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| 001 Become An Alumni.html |
944б |
| 001 Bonus Lecture.html |
1.18Кб |
| 001 Breaking The Flow.mp4 |
7.40Мб |
| 001 Breaking The Flow-en_US.srt |
3.01Кб |
| 001 Course Outline.mp4 |
77.28Мб |
| 001 Course Outline-en_US.srt |
8.85Кб |
| 001 Data Engineering Introduction.mp4 |
6.57Мб |
| 001 Data Engineering Introduction-en_US.srt |
4.28Кб |
| 001 Endorsements On LinkedIn.html |
2.05Кб |
| 001 Milestone Projects_.html |
738б |
| 001 Section Overview.mp4 |
6.34Мб |
| 001 Section Overview.mp4 |
1.89Мб |
| 001 Section Overview.mp4 |
3.57Мб |
| 001 Section Overview.mp4 |
8.09Мб |
| 001 Section Overview.mp4 |
2.79Мб |
| 001 Section Overview.mp4 |
5.57Мб |
| 001 Section Overview.mp4 |
3.25Мб |
| 001 Section Overview.mp4 |
3.67Мб |
| 001 Section Overview.mp4 |
4.33Мб |
| 001 Section Overview.mp4 |
3.41Мб |
| 001 Section Overview-en_US.srt |
4.79Кб |
| 001 Section Overview-en_US.srt |
2.05Кб |
| 001 Section Overview-en_US.srt |
3.69Кб |
| 001 Section Overview-en_US.srt |
3.25Кб |
| 001 Section Overview-en_US.srt |
2.64Кб |
| 001 Section Overview-en_US.srt |
3.98Кб |
| 001 Section Overview-en_US.srt |
3.16Кб |
| 001 Section Overview-en_US.srt |
1.89Кб |
| 001 Section Overview-en_US.srt |
2.85Кб |
| 001 Section Overview-en_US.srt |
3.40Кб |
| 001 Statistics and Mathematics.html |
710б |
| 001 The 2 Paths.mp4 |
4.26Мб |
| 001 The 2 Paths-en_US.srt |
4.69Кб |
| 001 What Is A Programming Language.mp4 |
18.83Мб |
| 001 What Is A Programming Language-en_US.srt |
7.26Кб |
| 001 What Is Machine Learning_.mp4 |
28.30Мб |
| 001 What Is Machine Learning_-en_US.srt |
8.96Кб |
| 002 AI_Machine Learning_Data Science.mp4 |
19.66Мб |
| 002 AI_Machine Learning_Data Science-en_US.srt |
6.45Кб |
| 002 Communicating Your Work.mp4 |
8.41Мб |
| 002 Communicating Your Work-en_US.srt |
4.85Кб |
| 002 Conditional Logic.mp4 |
56.54Мб |
| 002 Conditional Logic-en_US.srt |
16.39Кб |
| 002 Deep Learning and Unstructured Data.mp4 |
69.83Мб |
| 002 Deep Learning and Unstructured Data-en_US.srt |
20.97Кб |
| 002 Downloading Workbooks and Assignments.html |
967б |
| 002 Introducing Our Framework.mp4 |
4.20Мб |
| 002 Introducing Our Framework-en_US.srt |
3.70Кб |
| 002 Introducing Our Tools.mp4 |
19.27Мб |
| 002 Introducing Our Tools-en_US.srt |
4.50Кб |
| 002 Join Our Online Classroom_.html |
2.67Кб |
| 002 Matplotlib Introduction.mp4 |
20.90Мб |
| 002 Matplotlib Introduction-en_US.srt |
8.20Кб |
| 002 NumPy Introduction.mp4 |
13.63Мб |
| 002 NumPy Introduction-en_US.srt |
7.60Кб |
| 002 Project Overview.mp4 |
13.67Мб |
| 002 Project Overview.mp4 |
15.85Мб |
| 002 Project Overview-en_US.srt |
10.36Кб |
| 002 Project Overview-en_US.srt |
7.14Кб |
| 002 Python + Machine Learning Monthly.html |
917б |
| 002 Python Interpreter.mp4 |
68.54Мб |
| 002 Python Interpreter-en_US.srt |
8.75Кб |
| 002 Quick Note_ Upcoming Video.html |
587б |
| 002 Scikit-learn Introduction.mp4 |
17.17Мб |
| 002 Scikit-learn Introduction-en_US.srt |
10.94Кб |
| 002 Thank You.mp4 |
4.50Мб |
| 002 Thank You-en_US.srt |
3.73Кб |
| 002 What Is Data_.mp4 |
15.23Мб |
| 002 What Is Data_-en_US.srt |
7.95Кб |
| 003 6 Step Machine Learning Framework.mp4 |
23.45Мб |
| 003 6 Step Machine Learning Framework-en_US.srt |
6.87Кб |
| 003 Communicating With Managers.mp4 |
6.67Мб |
| 003 Communicating With Managers-en_US.srt |
4.51Кб |
| 003 Downloading the data for the next two projects.html |
1.64Кб |
| 003 Endorsements On LinkedIN.html |
2.05Кб |
| 003 Exercise_ Machine Learning Playground.mp4 |
42.57Мб |
| 003 Exercise_ Machine Learning Playground-en_US.srt |
8.13Кб |
| 003 Exercise_ Meet The Community.html |
3.04Кб |
| 003 How To Run Python Code.mp4 |
36.42Мб |
| 003 How To Run Python Code-en_US.srt |
6.83Кб |
| 003 Importing And Using Matplotlib.mp4 |
86.50Мб |
| 003 Importing And Using Matplotlib-en_US.srt |
16.68Кб |
| 003 Indentation In Python.mp4 |
11.31Мб |
| 003 Indentation In Python-en_US.srt |
5.47Кб |
| 003 Pandas Introduction.mp4 |
11.09Мб |
| 003 Pandas Introduction-en_US.srt |
7.01Кб |
| 003 Project Environment Setup.mp4 |
98.03Мб |
| 003 Project Environment Setup-en_US.srt |
15.17Кб |
| 003 Quick Note_ Correction In Next Video.html |
1.28Кб |
| 003 Quick Note_ Upcoming Video.html |
390б |
| 003 Setting Up With Google.html |
568б |
| 003 Thank You Part 2.html |
730б |
| 003 What If I Don't Have Enough Experience__en.vtt |
17.83Кб |
| 003 What If I Don't Have Enough Experience_.mp4 |
147.35Мб |
| 003 What If I Don't Have Enough Experience_-en_US.srt |
5.16Кб |
| 003 What Is A Data Engineer_.mp4 |
9.50Мб |
| 003 What Is A Data Engineer_-en_US.srt |
5.13Кб |
| 003 What is Conda_.mp4 |
12.46Мб |
| 003 What is Conda_-en_US.srt |
3.46Кб |
| 004 Anatomy Of A Matplotlib Figure.mp4 |
53.21Мб |
| 004 Anatomy Of A Matplotlib Figure-en_US.srt |
14.54Кб |
| 004 Communicating With Co-Workers.mp4 |
7.34Мб |
| 004 Communicating With Co-Workers-en_US.srt |
5.48Кб |
| 004 Conda Environments.mp4 |
14.62Мб |
| 004 Conda Environments-en_US.srt |
6.22Кб |
| 004 How Did We Get Here_.mp4 |
30.50Мб |
| 004 How Did We Get Here_-en_US.srt |
7.34Кб |
| 004 Learning Guideline.html |
336б |
| 004 NumPy DataTypes and Attributes.mp4 |
56.56Мб |
| 004 NumPy DataTypes and Attributes-en_US.srt |
20.04Кб |
| 004 Optional_ Windows Project Environment Setup.mp4 |
34.50Мб |
| 004 Optional_ Windows Project Environment Setup-en_US.srt |
5.56Кб |
| 004 Our First Python Program.mp4 |
29.85Мб |
| 004 Our First Python Program-en_US.srt |
9.07Кб |
| 004 Project Environment Setup.mp4 |
99.11Мб |
| 004 Project Environment Setup-en_US.srt |
16.26Кб |
| 004 Refresher_ What Is Machine Learning_.mp4 |
17.85Мб |
| 004 Refresher_ What Is Machine Learning_-en_US.srt |
6.69Кб |
| 004 Series, Data Frames and CSVs.mp4 |
91.09Мб |
| 004 Series, Data Frames and CSVs-en_US.srt |
18.45Кб |
| 004 Setting Up Google Colab.mp4 |
73.72Мб |
| 004 Setting Up Google Colab-en_US.srt |
10.33Кб |
| 004 Truthy vs Falsey.mp4 |
36.35Мб |
| 004 Truthy vs Falsey-en_US.srt |
6.39Кб |
| 004 Types of Machine Learning Problems.mp4 |
20.98Мб |
| 004 Types of Machine Learning Problems-en_US.srt |
14.46Кб |
| 004 What Is A Data Engineer 2_.mp4 |
24.21Мб |
| 004 What Is A Data Engineer 2_-en_US.srt |
6.53Кб |
| 004 Your First Day.mp4 |
7.27Мб |
| 004 Your First Day-en_US.srt |
5.37Кб |
| 005 Creating NumPy Arrays.mp4 |
56.09Мб |
| 005 Creating NumPy Arrays-en_US.srt |
12.46Кб |
| 005 Data from URLs.html |
1.13Кб |
| 005 Exercise_ YouTube Recommendation Engine.mp4 |
8.89Мб |
| 005 Exercise_ YouTube Recommendation Engine-en_US.srt |
5.62Кб |
| 005 Google Colab Workspace.mp4 |
32.23Мб |
| 005 Google Colab Workspace-en_US.srt |
6.33Кб |
| 005 Latest Version Of Python.mp4 |
6.99Мб |
| 005 Latest Version Of Python-en_US.srt |
2.69Кб |
| 005 Mac Environment Setup.mp4 |
139.56Мб |
| 005 Mac Environment Setup-en_US.srt |
25.80Кб |
| 005 Quick Note_ Upcoming Videos.html |
1018б |
| 005 Quick Note_ Upcoming Videos.html |
565б |
| 005 Scatter Plot And Bar Plot.mp4 |
44.60Мб |
| 005 Scatter Plot And Bar Plot-en_US.srt |
14.91Кб |
| 005 Step 1~4 Framework Setup.mp4 |
102.28Мб |
| 005 Step 1~4 Framework Setup.mp4 |
84.12Мб |
| 005 Step 1~4 Framework Setup-en_US.srt |
17.54Кб |
| 005 Step 1~4 Framework Setup-en_US.srt |
12.51Кб |
| 005 Ternary Operator.mp4 |
8.32Мб |
| 005 Ternary Operator-en_US.srt |
4.98Кб |
| 005 Types of Data.mp4 |
20.01Мб |
| 005 Types of Data-en_US.srt |
6.49Кб |
| 005 Weekend Project Principle.mp4 |
10.31Мб |
| 005 Weekend Project Principle-en_US.srt |
9.00Кб |
| 005 What Is A Data Engineer 3_.mp4 |
13.14Мб |
| 005 What Is A Data Engineer 3_-en_US.srt |
5.64Кб |
| 006 Communicating With Outside World.mp4 |
6.29Мб |
| 006 Communicating With Outside World-en_US.srt |
4.60Кб |
| 006 Describing Data with Pandas.mp4 |
51.19Мб |
| 006 Describing Data with Pandas-en_US.srt |
14.23Кб |
| 006 Exploring Our Data.mp4 |
135.50Мб |
| 006 Exploring Our Data-en_US.srt |
21.39Кб |
| 006 Getting Our Tools Ready.mp4 |
76.81Мб |
| 006 Getting Our Tools Ready-en_US.srt |
13.03Кб |
| 006 Histograms And Subplots.mp4 |
57.48Мб |
| 006 Histograms And Subplots-en_US.srt |
13.01Кб |
| 006 JTS_ Learn to Learn.mp4 |
2.65Мб |
| 006 JTS_ Learn to Learn-en_US.srt |
2.44Кб |
| 006 Mac Environment Setup 2.mp4 |
122.18Мб |
| 006 Mac Environment Setup 2-en_US.srt |
21.74Кб |
| 006 NumPy Random Seed.mp4 |
36.46Мб |
| 006 NumPy Random Seed-en_US.srt |
10.45Кб |
| 006 Python 2 vs Python 3.mp4 |
65.78Мб |
| 006 Python 2 vs Python 3-en_US.srt |
8.40Кб |
| 006 Scikit-learn Cheatsheet.mp4 |
75.12Мб |
| 006 Scikit-learn Cheatsheet-en_US.srt |
10.51Кб |
| 006 Short Circuiting.mp4 |
8.15Мб |
| 006 Short Circuiting-en_US.srt |
4.80Кб |
| 006 Types of Evaluation.mp4 |
6.52Мб |
| 006 Types of Evaluation-en_US.srt |
4.56Кб |
| 006 Types of Machine Learning.mp4 |
9.63Мб |
| 006 Types of Machine Learning-en_US.srt |
5.51Кб |
| 006 Uploading Project Data.mp4 |
50.16Мб |
| 006 Uploading Project Data-en_US.srt |
9.47Кб |
| 006 What Is A Data Engineer 4_.mp4 |
7.43Мб |
| 006 What Is A Data Engineer 4_-en_US.srt |
4.01Кб |
| 007 Are You Getting It Yet_.html |
160б |
| 007 Exercise_ How Does Python Work_.mp4 |
9.34Мб |
| 007 Exercise_ How Does Python Work_-en_US.srt |
2.96Кб |
| 007 Exploring Our Data.mp4 |
64.46Мб |
| 007 Exploring Our Data 2.mp4 |
50.70Мб |
| 007 Exploring Our Data 2-en_US.srt |
8.86Кб |
| 007 Exploring Our Data-en_US.srt |
11.75Кб |
| 007 Features In Data.mp4 |
14.84Мб |
| 007 Features In Data-en_US.srt |
6.88Кб |
| 007 JTS_ Start With Why.mp4 |
7.45Мб |
| 007 JTS_ Start With Why-en_US.srt |
2.94Кб |
| 007 Logical Operators.mp4 |
14.60Мб |
| 007 Logical Operators-en_US.srt |
8.63Кб |
| 007 Selecting and Viewing Data with Pandas.mp4 |
61.67Мб |
| 007 Selecting and Viewing Data with Pandas-en_US.srt |
15.22Кб |
| 007 Setting Up Our Data.mp4 |
41.41Мб |
| 007 Setting Up Our Data-en_US.srt |
6.67Кб |
| 007 Storytelling.mp4 |
4.86Мб |
| 007 Storytelling-en_US.srt |
4.12Кб |
| 007 Subplots Option 2.mp4 |
31.24Мб |
| 007 Subplots Option 2-en_US.srt |
6.65Кб |
| 007 Types Of Databases.mp4 |
24.34Мб |
| 007 Types Of Databases-en_US.srt |
8.82Кб |
| 007 Typical scikit-learn Workflow_en.vtt |
28.43Кб |
| 007 Typical scikit-learn Workflow.mp4 |
184.59Мб |
| 007 Typical scikit-learn Workflow-en_US.srt |
2.42Кб |
| 007 Viewing Arrays and Matrices.mp4 |
59.36Мб |
| 007 Viewing Arrays and Matrices-en_US.srt |
13.86Кб |
| 007 Windows Environment Setup.mp4 |
32.91Мб |
| 007 Windows Environment Setup-en_US.srt |
7.89Кб |
| 008 Communicating and sharing your work_ Further reading.html |
3.12Кб |
| 008 Exercise_ Logical Operators.mp4 |
19.03Мб |
| 008 Exercise_ Logical Operators-en_US.srt |
8.69Кб |
| 008 Feature Engineering.mp4 |
157.40Мб |
| 008 Feature Engineering-en_US.srt |
22.32Кб |
| 008 Finding Patterns.mp4 |
60.29Мб |
| 008 Finding Patterns-en_US.srt |
13.67Кб |
| 008 Learning Python.mp4 |
6.56Мб |
| 008 Learning Python-en_US.srt |
2.72Кб |
| 008 Manipulating Arrays.mp4 |
68.48Мб |
| 008 Manipulating Arrays-en_US.srt |
17.15Кб |
| 008 Modelling - Splitting Data.mp4 |
11.30Мб |
| 008 Modelling - Splitting Data-en_US.srt |
7.80Кб |
| 008 Optional_ Debugging Warnings In Jupyter.mp4 |
171.49Мб |
| 008 Optional_ Debugging Warnings In Jupyter-en_US.srt |
26.84Кб |
| 008 Quick Note_ Upcoming Video.html |
481б |
| 008 Quick Note_ Upcoming Videos.html |
352б |
| 008 Quick Tip_ Data Visualizations.mp4 |
4.35Мб |
| 008 Quick Tip_ Data Visualizations-en_US.srt |
2.31Кб |
| 008 Selecting and Viewing Data with Pandas Part 2.mp4 |
103.45Мб |
| 008 Selecting and Viewing Data with Pandas Part 2-en_US.srt |
18.95Кб |
| 008 Setting Up Our Data 2.mp4 |
20.99Мб |
| 008 Setting Up Our Data 2-en_US.srt |
2.31Кб |
| 008 What Is Machine Learning_ Round 2.mp4 |
11.85Мб |
| 008 What Is Machine Learning_ Round 2-en_US.srt |
6.25Кб |
| 008 Windows Environment Setup 2.mp4 |
190.92Мб |
| 008 Windows Environment Setup 2-en_US.srt |
33.25Кб |
| 009 CWD_ Git + Github.mp4 |
176.27Мб |
| 009 CWD_ Git + Github-en_US.srt |
21.45Кб |
| 009 Finding Patterns 2.mp4 |
94.32Мб |
| 009 Finding Patterns 2-en_US.srt |
24.16Кб |
| 009 Getting Your Data Ready_ Splitting Your Data_en.vtt |
10.65Кб |
| 009 Getting Your Data Ready_ Splitting Your Data.mp4 |
61.01Мб |
| 009 Getting Your Data Ready_ Splitting Your Data-en_US.srt |
7.23Кб |
| 009 Importing TensorFlow 2.mp4 |
114.44Мб |
| 009 Importing TensorFlow 2-en_US.srt |
17.98Кб |
| 009 is vs ==.mp4 |
15.08Мб |
| 009 is vs ==-en_US.srt |
8.85Кб |
| 009 Linux Environment Setup.html |
1.03Кб |
| 009 Manipulating Arrays 2.mp4 |
57.97Мб |
| 009 Manipulating Arrays 2-en_US.srt |
12.01Кб |
| 009 Manipulating Data.mp4 |
100.85Мб |
| 009 Manipulating Data-en_US.srt |
18.56Кб |
| 009 Modelling - Picking the Model.mp4 |
8.74Мб |
| 009 Modelling - Picking the Model-en_US.srt |
6.24Кб |
| 009 Optional_ OLTP Databases.mp4 |
68.24Мб |
| 009 Optional_ OLTP Databases-en_US.srt |
12.65Кб |
| 009 Plotting From Pandas DataFrames.mp4 |
49.46Мб |
| 009 Plotting From Pandas DataFrames-en_US.srt |
9.68Кб |
| 009 Python Data Types.mp4 |
11.93Мб |
| 009 Python Data Types-en_US.srt |
5.72Кб |
| 009 Section Review.mp4 |
2.25Мб |
| 009 Section Review-en_US.srt |
2.20Кб |
| 009 Turning Data Into Numbers.mp4 |
144.16Мб |
| 009 Turning Data Into Numbers-en_US.srt |
22.81Кб |
| 010 CWD_ Git + Github 2.mp4 |
102.62Мб |
| 010 CWD_ Git + Github 2-en_US.srt |
19.47Кб |
| 010 Filling Missing Numerical Values.mp4 |
103.42Мб |
| 010 Filling Missing Numerical Values-en_US.srt |
17.60Кб |
| 010 Finding Patterns 3.mp4 |
135.93Мб |
| 010 Finding Patterns 3-en_US.srt |
19.49Кб |
| 010 For Loops.mp4 |
16.43Мб |
| 010 For Loops-en_US.srt |
8.13Кб |
| 010 How To Succeed.html |
280б |
| 010 Manipulating Data 2.mp4 |
84.31Мб |
| 010 Manipulating Data 2-en_US.srt |
14.82Кб |
| 010 Modelling - Tuning.mp4 |
15.98Мб |
| 010 Modelling - Tuning-en_US.srt |
5.09Кб |
| 010 Monthly Coding Challenges, Free Resources and Guides.html |
1.63Кб |
| 010 Optional_ Learn SQL.html |
410б |
| 010 Optional_ TensorFlow 2.0 Default Issue.mp4 |
13.98Мб |
| 010 Optional_ TensorFlow 2.0 Default Issue-en_US.srt |
4.62Кб |
| 010 Quick Note_ Regular Expressions.html |
632б |
| 010 Quick Tip_ Clean, Transform, Reduce.mp4 |
9.74Мб |
| 010 Quick Tip_ Clean, Transform, Reduce-en_US.srt |
6.55Кб |
| 010 Sharing your Conda Environment.html |
2.41Кб |
| 010 Standard Deviation and Variance.mp4 |
36.79Мб |
| 010 Standard Deviation and Variance-en_US.srt |
9.82Кб |
| 011 Contributing To Open Source.mp4 |
109.38Мб |
| 011 Contributing To Open Source-en_US.srt |
17.44Кб |
| 011 Filling Missing Categorical Values.mp4 |
64.59Мб |
| 011 Filling Missing Categorical Values-en_US.srt |
11.36Кб |
| 011 Getting Your Data Ready_ Convert Data To Numbers.mp4 |
130.89Мб |
| 011 Getting Your Data Ready_ Convert Data To Numbers-en_US.srt |
23.40Кб |
| 011 Hadoop, HDFS and MapReduce.mp4 |
5.11Мб |
| 011 Hadoop, HDFS and MapReduce-en_US.srt |
4.94Кб |
| 011 Iterables.mp4 |
23.53Мб |
| 011 Iterables-en_US.srt |
7.27Кб |
| 011 Jupyter Notebook Walkthrough.mp4 |
56.79Мб |
| 011 Jupyter Notebook Walkthrough-en_US.srt |
15.85Кб |
| 011 Manipulating Data 3.mp4 |
76.80Мб |
| 011 Manipulating Data 3-en_US.srt |
14.01Кб |
| 011 Modelling - Comparison.mp4 |
18.23Мб |
| 011 Modelling - Comparison-en_US.srt |
13.32Кб |
| 011 Numbers.mp4 |
55.05Мб |
| 011 Numbers-en_US.srt |
12.02Кб |
| 011 Plotting From Pandas DataFrames 2.mp4 |
97.29Мб |
| 011 Plotting From Pandas DataFrames 2-en_US.srt |
13.52Кб |
| 011 Preparing Our Data For Machine Learning.mp4 |
70.41Мб |
| 011 Preparing Our Data For Machine Learning-en_US.srt |
13.11Кб |
| 011 Reshape and Transpose.mp4 |
51.39Мб |
| 011 Reshape and Transpose-en_US.srt |
9.68Кб |
| 011 Using A GPU.mp4 |
78.88Мб |
| 011 Using A GPU-en_US.srt |
12.98Кб |
| 012 Apache Spark and Apache Flink.mp4 |
2.63Мб |
| 012 Apache Spark and Apache Flink-en_US.srt |
2.39Кб |
| 012 Assignment_ Pandas Practice.html |
2.05Кб |
| 012 Choosing The Right Models.mp4 |
96.34Мб |
| 012 Choosing The Right Models-en_US.srt |
14.17Кб |
| 012 Contributing To Open Source 2.mp4 |
112.99Мб |
| 012 Contributing To Open Source 2-en_US.srt |
10.41Кб |
| 012 Dot Product vs Element Wise.mp4 |
83.66Мб |
| 012 Dot Product vs Element Wise-en_US.srt |
15.89Кб |
| 012 Exercise_ Tricky Counter.mp4 |
5.52Мб |
| 012 Exercise_ Tricky Counter-en_US.srt |
3.84Кб |
| 012 Fitting A Machine Learning Model.mp4 |
53.52Мб |
| 012 Fitting A Machine Learning Model-en_US.srt |
11.10Кб |
| 012 Jupyter Notebook Walkthrough 2.mp4 |
87.64Мб |
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22.66Кб |
| 012 Math Functions.mp4 |
25.91Мб |
| 012 Math Functions-en_US.srt |
5.58Кб |
| 012 Note_ Update to next video (OneHotEncoder can handle NaN_None values).html |
1.57Кб |
| 012 Optional_ GPU and Google Colab.mp4 |
38.31Мб |
| 012 Optional_ GPU and Google Colab-en_US.srt |
6.34Кб |
| 012 Overfitting and Underfitting Definitions.html |
1.95Кб |
| 012 Plotting from Pandas DataFrames 3.mp4 |
73.38Мб |
| 012 Plotting from Pandas DataFrames 3-en_US.srt |
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| 013 Coding Challenges.html |
948б |
| 013 DEVELOPER FUNDAMENTALS_ I.mp4 |
47.71Мб |
| 013 DEVELOPER FUNDAMENTALS_ I-en_US.srt |
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| 013 Exercise_ Nut Butter Store Sales.mp4 |
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| 013 Exercise_ Nut Butter Store Sales-en_US.srt |
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| 013 Experimentation.mp4 |
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| 013 Experimenting With Machine Learning Models.mp4 |
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| 013 Experimenting With Machine Learning Models-en_US.srt |
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| 013 Getting Your Data Ready_ Handling Missing Values With Pandas.mp4 |
45.56Мб |
| 013 Getting Your Data Ready_ Handling Missing Values With Pandas-en_US.srt |
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| 013 How To Download The Course Assignments.mp4 |
64.62Мб |
| 013 How To Download The Course Assignments-en_US.srt |
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| 013 Jupyter Notebook Walkthrough 3.mp4 |
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| 013 Jupyter Notebook Walkthrough 3-en_US.srt |
12.01Кб |
| 013 Kafka and Stream Processing.mp4 |
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| 013 Kafka and Stream Processing-en_US.srt |
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| 013 Optional_ Reloading Colab Notebook.mp4 |
71.87Мб |
| 013 Optional_ Reloading Colab Notebook-en_US.srt |
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| 013 Plotting from Pandas DataFrames 4.mp4 |
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| 013 Plotting from Pandas DataFrames 4-en_US.srt |
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| 013 range().mp4 |
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| 013 range()-en_US.srt |
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| 013 Splitting Data.mp4 |
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| 013 Splitting Data-en_US.srt |
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| 014 Challenge_ What's wrong with splitting data after filling it_.html |
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| 014 Comparison Operators.mp4 |
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| 014 Comparison Operators-en_US.srt |
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| 014 enumerate().mp4 |
9.40Мб |
| 014 enumerate()-en_US.srt |
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| 014 Exercise_ Contribute To Open Source.html |
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| 014 Extension_ Feature Scaling.html |
2.93Кб |
| 014 Loading Our Data Labels.mp4 |
112.36Мб |
| 014 Loading Our Data Labels-en_US.srt |
16.29Кб |
| 014 Operator Precedence.mp4 |
5.78Мб |
| 014 Operator Precedence-en_US.srt |
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| 014 Plotting from Pandas DataFrames 5.mp4 |
54.39Мб |
| 014 Plotting from Pandas DataFrames 5-en_US.srt |
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| 014 Tools We Will Use.mp4 |
12.91Мб |
| 014 Tools We Will Use-en_US.srt |
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| 014 Tuning_Improving Our Model.mp4 |
102.85Мб |
| 014 Tuning_Improving Our Model-en_US.srt |
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| 015 Custom Evaluation Function_en.vtt |
14.40Кб |
| 015 Custom Evaluation Function.mp4 |
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| 015 Custom Evaluation Function-en_US.srt |
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| 015 Exercise_ Operator Precedence.html |
683б |
| 015 Note_ Correction in the upcoming video (splitting data).html |
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| 015 Optional_ Elements of AI.html |
975б |
| 015 Plotting from Pandas DataFrames 6.mp4 |
67.47Мб |
| 015 Plotting from Pandas DataFrames 6-en_US.srt |
11.73Кб |
| 015 Preparing The Images.mp4 |
132.05Мб |
| 015 Preparing The Images-en_US.srt |
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| 015 Sorting Arrays.mp4 |
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| 015 Sorting Arrays-en_US.srt |
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| 015 Tuning Hyperparameters.mp4 |
106.28Мб |
| 015 Tuning Hyperparameters-en_US.srt |
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| 015 While Loops.mp4 |
13.94Мб |
| 015 While Loops-en_US.srt |
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| 016 Getting Your Data Ready_ Handling Missing Values With Scikit-learn.mp4 |
131.36Мб |
| 016 Getting Your Data Ready_ Handling Missing Values With Scikit-learn-en_US.srt |
24.78Кб |
| 016 Optional_ bin() and complex.mp4 |
10.65Мб |
| 016 Optional_ bin() and complex-en_US.srt |
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| 016 Plotting from Pandas DataFrames 7.mp4 |
118.88Мб |
| 016 Plotting from Pandas DataFrames 7-en_US.srt |
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| 016 Reducing Data.mp4 |
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| 016 Reducing Data-en_US.srt |
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| 016 Tuning Hyperparameters 2.mp4 |
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| 016 Tuning Hyperparameters 2-en_US.srt |
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| 016 Turn Images Into NumPy Arrays.mp4 |
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| 016 Turn Images Into NumPy Arrays-en_US.srt |
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| 016 Turning Data Labels Into Numbers.mp4 |
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| 016 Turning Data Labels Into Numbers-en_US.srt |
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| 016 While Loops 2.mp4 |
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| 017 Assignment_ NumPy Practice.html |
2.17Кб |
| 017 break, continue, pass.mp4 |
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| 017 break, continue, pass-en_US.srt |
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| 017 Creating Our Own Validation Set.mp4 |
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| 017 Creating Our Own Validation Set-en_US.srt |
11.76Кб |
| 017 Customizing Your Plots.mp4 |
90.98Мб |
| 017 Customizing Your Plots-en_US.srt |
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| 017 NEW_ Choosing The Right Model For Your Data.mp4 |
234.28Мб |
| 017 NEW_ Choosing The Right Model For Your Data-en_US.srt |
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| 017 RandomizedSearchCV.mp4 |
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| 017 Tuning Hyperparameters 3.mp4 |
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| 017 Tuning Hyperparameters 3-en_US.srt |
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| 017 Variables.mp4 |
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| 017 Variables-en_US.srt |
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| 018 Customizing Your Plots 2.mp4 |
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| 018 Customizing Your Plots 2-en_US.srt |
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| 018 Expressions vs Statements.mp4 |
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| 018 Expressions vs Statements-en_US.srt |
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| 018 Improving Hyperparameters.mp4 |
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| 018 Improving Hyperparameters-en_US.srt |
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| 018 NEW_ Choosing The Right Model For Your Data 2 (Regression).mp4 |
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| 018 NEW_ Choosing The Right Model For Your Data 2 (Regression)-en_US.srt |
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| 018 Optional_ Extra NumPy resources.html |
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| 018 Our First GUI.mp4 |
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| 018 Our First GUI-en_US.srt |
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| 018 Preprocess Images.mp4 |
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| 018 Preprocess Images-en_US.srt |
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| 018 Quick Note_ Confusion Matrix Labels.html |
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| 019 Augmented Assignment Operator.mp4 |
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| 019 Augmented Assignment Operator-en_US.srt |
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| 019 DEVELOPER FUNDAMENTALS_ IV.mp4 |
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| 019 DEVELOPER FUNDAMENTALS_ IV-en_US.srt |
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| 019 Evaluating Our Model.mp4 |
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| 019 Evaluating Our Model-en_US.srt |
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| 019 Preproccessing Our Data.mp4 |
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| 019 Preproccessing Our Data-en_US.srt |
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| 019 Preprocess Images 2.mp4 |
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| 019 Preprocess Images 2-en_US.srt |
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| 019 Quick Note_ Decision Trees.html |
221б |
| 019 Saving And Sharing Your Plots.mp4 |
49.62Мб |
| 019 Saving And Sharing Your Plots-en_US.srt |
6.24Кб |
| 020 Assignment_ Matplotlib Practice.html |
2.05Кб |
| 020 Evaluating Our Model 2.mp4 |
34.64Мб |
| 020 Evaluating Our Model 2-en_US.srt |
8.07Кб |
| 020 Exercise_ Find Duplicates.mp4 |
8.50Мб |
| 020 Exercise_ Find Duplicates-en_US.srt |
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| 020 Making Predictions.mp4 |
77.41Мб |
| 020 Making Predictions-en_US.srt |
11.25Кб |
| 020 Quick Tip_ How ML Algorithms Work.mp4 |
2.78Мб |
| 020 Quick Tip_ How ML Algorithms Work-en_US.srt |
1.88Кб |
| 020 Strings.mp4 |
11.19Мб |
| 020 Strings-en_US.srt |
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| 020 Turning Data Into Batches.mp4 |
74.59Мб |
| 020 Turning Data Into Batches-en_US.srt |
12.36Кб |
| 021 Choosing The Right Model For Your Data 3 (Classification).mp4 |
115.87Мб |
| 021 Choosing The Right Model For Your Data 3 (Classification)-en_US.srt |
18.55Кб |
| 021 Evaluating Our Model 3.mp4 |
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| 021 Evaluating Our Model 3-en_US.srt |
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| 021 Feature Importance.mp4 |
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| 021 Feature Importance-en_US.srt |
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| 021 Functions.mp4 |
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| 021 Functions-en_US.srt |
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| 021 String Concatenation.mp4 |
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| 021 String Concatenation-en_US.srt |
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| 021 Turning Data Into Batches 2.mp4 |
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| 021 Turning Data Into Batches 2-en_US.srt |
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| 022 Finding The Most Important Features.mp4 |
123.68Мб |
| 022 Finding The Most Important Features-en_US.srt |
23.62Кб |
| 022 Fitting A Model To The Data.mp4 |
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| 022 Fitting A Model To The Data-en_US.srt |
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| 022 Parameters and Arguments.mp4 |
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| 022 Type Conversion.mp4 |
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| 022 Type Conversion-en_US.srt |
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| 022 Visualizing Our Data.mp4 |
120.06Мб |
| 022 Visualizing Our Data-en_US.srt |
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| 023 Default Parameters and Keyword Arguments.mp4 |
18.12Мб |
| 023 Default Parameters and Keyword Arguments-en_US.srt |
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| 023 Escape Sequences.mp4 |
8.68Мб |
| 023 Escape Sequences-en_US.srt |
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| 023 Making Predictions With Our Model.mp4 |
64.10Мб |
| 023 Making Predictions With Our Model-en_US.srt |
12.91Кб |
| 023 Preparing Our Inputs and Outputs.mp4 |
47.96Мб |
| 023 Preparing Our Inputs and Outputs-en_US.srt |
8.03Кб |
| 023 Reviewing The Project.mp4 |
84.78Мб |
| 023 Reviewing The Project-en_US.srt |
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| 024 Formatted Strings.mp4 |
21.81Мб |
| 024 Formatted Strings-en_US.srt |
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| 024 Optional_ How machines learn and what's going on behind the scenes_.html |
2.72Кб |
| 024 predict() vs predict_proba().mp4 |
39.07Мб |
| 024 predict() vs predict_proba()-en_US.srt |
12.19Кб |
| 024 return.mp4 |
36.79Мб |
| 024 return-en_US.srt |
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| 025 Building A Deep Learning Model.mp4 |
120.15Мб |
| 025 Building A Deep Learning Model-en_US.srt |
17.32Кб |
| 025 Exercise_ Tesla.html |
402б |
| 025 NEW_ Making Predictions With Our Model (Regression).mp4 |
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| 025 NEW_ Making Predictions With Our Model (Regression)-en_US.srt |
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| 025 String Indexes.mp4 |
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| 025 String Indexes-en_US.srt |
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| 026 Building A Deep Learning Model 2.mp4 |
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| 026 Building A Deep Learning Model 2-en_US.srt |
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| 026 Immutability.mp4 |
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| 026 Immutability-en_US.srt |
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| 026 Methods vs Functions.mp4 |
26.33Мб |
| 026 Methods vs Functions-en_US.srt |
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| 026 NEW_ Evaluating A Machine Learning Model (Score) Part 1.mp4 |
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| 026 NEW_ Evaluating A Machine Learning Model (Score) Part 1-en_US.srt |
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| 027 Building A Deep Learning Model 3.mp4 |
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| 027 Building A Deep Learning Model 3-en_US.srt |
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| 027 Built-In Functions + Methods.mp4 |
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| 027 Built-In Functions + Methods-en_US.srt |
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| 027 Docstrings.mp4 |
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| 027 Docstrings-en_US.srt |
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| 027 NEW_ Evaluating A Machine Learning Model (Score) Part 2.mp4 |
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| 027 NEW_ Evaluating A Machine Learning Model (Score) Part 2-en_US.srt |
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| 028 Booleans.mp4 |
7.45Мб |
| 028 Booleans-en_US.srt |
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| 028 Building A Deep Learning Model 4.mp4 |
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| 028 Building A Deep Learning Model 4-en_US.srt |
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| 028 Clean Code.mp4 |
17.58Мб |
| 028 Clean Code-en_US.srt |
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| 028 Evaluating A Machine Learning Model 2 (Cross Validation).mp4 |
81.47Мб |
| 028 Evaluating A Machine Learning Model 2 (Cross Validation)-en_US.srt |
18.35Кб |
| 029 _args and __kwargs.mp4 |
32.78Мб |
| 029 _args and __kwargs-en_US.srt |
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| 029 Evaluating A Classification Model 1 (Accuracy).mp4 |
29.87Мб |
| 029 Evaluating A Classification Model 1 (Accuracy)-en_US.srt |
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| 029 Exercise_ Type Conversion.mp4 |
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| 029 Exercise_ Type Conversion-en_US.srt |
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| 029 Summarizing Our Model.mp4 |
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| 029 Summarizing Our Model-en_US.srt |
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| 030 DEVELOPER FUNDAMENTALS_ II.mp4 |
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| 030 DEVELOPER FUNDAMENTALS_ II-en_US.srt |
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| 030 Evaluating A Classification Model 2 (ROC Curve).mp4 |
56.34Мб |
| 030 Evaluating A Classification Model 2 (ROC Curve)-en_US.srt |
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| 030 Evaluating Our Model.mp4 |
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| 030 Evaluating Our Model-en_US.srt |
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| 030 Exercise_ Functions.mp4 |
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| 030 Exercise_ Functions-en_US.srt |
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| 031 Evaluating A Classification Model 3 (ROC Curve).mp4 |
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| 031 Evaluating A Classification Model 3 (ROC Curve)-en_US.srt |
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| 031 Exercise_ Password Checker.mp4 |
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| 031 Exercise_ Password Checker-en_US.srt |
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| 031 Preventing Overfitting.mp4 |
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| 031 Preventing Overfitting-en_US.srt |
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| 031 Scope.mp4 |
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| 031 Scope-en_US.srt |
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| 032 Lists.mp4 |
8.90Мб |
| 032 Lists-en_US.srt |
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| 032 Reading Extension_ ROC Curve + AUC.html |
1.48Кб |
| 032 Scope Rules.mp4 |
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| 032 Scope Rules-en_US.srt |
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| 032 Training Your Deep Neural Network.mp4 |
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| 032 Training Your Deep Neural Network-en_US.srt |
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| 033 Evaluating A Classification Model 4 (Confusion Matrix).mp4 |
77.69Мб |
| 033 Evaluating A Classification Model 4 (Confusion Matrix)-en_US.srt |
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| 033 Evaluating Performance With TensorBoard.mp4 |
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| 033 Evaluating Performance With TensorBoard-en_US.srt |
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| 033 global Keyword.mp4 |
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| 033 global Keyword-en_US.srt |
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| 033 List Slicing.mp4 |
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| 033 List Slicing-en_US.srt |
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| 034 Make And Transform Predictions.mp4 |
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| 034 Make And Transform Predictions-en_US.srt |
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| 034 Matrix.mp4 |
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| 034 Matrix-en_US.srt |
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| 034 NEW_ Evaluating A Classification Model 5 (Confusion Matrix).mp4 |
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| 034 NEW_ Evaluating A Classification Model 5 (Confusion Matrix)-en_US.srt |
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| 034 nonlocal Keyword.mp4 |
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| 034 nonlocal Keyword-en_US.srt |
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| 035 Evaluating A Classification Model 6 (Classification Report)_en.vtt |
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| 035 Evaluating A Classification Model 6 (Classification Report).mp4 |
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| 035 Evaluating A Classification Model 6 (Classification Report)-en_US.srt |
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| 035 List Methods.mp4 |
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| 035 List Methods-en_US.srt |
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| 035 Transform Predictions To Text.mp4 |
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| 035 Transform Predictions To Text-en_US.srt |
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| 035 Why Do We Need Scope_.mp4 |
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| 035 Why Do We Need Scope_-en_US.srt |
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| 036 List Methods 2.mp4 |
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| 036 List Methods 2-en_US.srt |
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| 036 NEW_ Evaluating A Regression Model 1 (R2 Score).mp4 |
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| 036 NEW_ Evaluating A Regression Model 1 (R2 Score)-en_US.srt |
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| 036 Pure Functions.mp4 |
30.01Мб |
| 036 Pure Functions-en_US.srt |
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| 036 Visualizing Model Predictions.mp4 |
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| 036 Visualizing Model Predictions-en_US.srt |
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| 037 List Methods 3.mp4 |
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| 037 List Methods 3-en_US.srt |
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| 037 map().mp4 |
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| 037 map()-en_US.srt |
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| 037 NEW_ Evaluating A Regression Model 2 (MAE).mp4 |
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| 037 NEW_ Evaluating A Regression Model 2 (MAE)-en_US.srt |
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| 037 Visualizing And Evaluate Model Predictions 2.mp4 |
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| 037 Visualizing And Evaluate Model Predictions 2-en_US.srt |
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| 038 Common List Patterns.mp4 |
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| 038 Common List Patterns-en_US.srt |
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| 038 filter().mp4 |
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| 038 filter()-en_US.srt |
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| 038 NEW_ Evaluating A Regression Model 3 (MSE).mp4 |
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| 038 NEW_ Evaluating A Regression Model 3 (MSE)-en_US.srt |
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| 038 Visualizing And Evaluate Model Predictions 3.mp4 |
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| 038 Visualizing And Evaluate Model Predictions 3-en_US.srt |
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| 039 List Unpacking.mp4 |
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| 039 List Unpacking-en_US.srt |
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| 039 Machine Learning Model Evaluation.html |
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| 039 Saving And Loading A Trained Model.mp4 |
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| 039 Saving And Loading A Trained Model-en_US.srt |
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| 039 zip().mp4 |
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| 039 zip()-en_US.srt |
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| 040 NEW_ Evaluating A Model With Cross Validation and Scoring Parameter.mp4 |
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| 040 NEW_ Evaluating A Model With Cross Validation and Scoring Parameter-en_US.srt |
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| 040 None.mp4 |
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| 040 None-en_US.srt |
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| 040 reduce().mp4 |
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| 040 reduce()-en_US.srt |
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| 040 Training Model On Full Dataset.mp4 |
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| 040 Training Model On Full Dataset-en_US.srt |
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| 041 Dictionaries.mp4 |
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| 041 Dictionaries-en_US.srt |
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| 041 List Comprehensions.mp4 |
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| 041 List Comprehensions-en_US.srt |
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| 041 Making Predictions On Test Images.mp4 |
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| 041 Making Predictions On Test Images-en_US.srt |
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| 041 NEW_ Evaluating A Model With Scikit-learn Functions.mp4 |
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| 041 NEW_ Evaluating A Model With Scikit-learn Functions-en_US.srt |
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| 042 DEVELOPER FUNDAMENTALS_ III.mp4 |
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| 042 DEVELOPER FUNDAMENTALS_ III-en_US.srt |
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| 042 Improving A Machine Learning Model.mp4 |
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| 042 Improving A Machine Learning Model-en_US.srt |
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| 042 Set Comprehensions.mp4 |
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| 042 Set Comprehensions-en_US.srt |
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| 042 Submitting Model to Kaggle.mp4 |
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| 042 Submitting Model to Kaggle-en_US.srt |
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| 043 Dictionary Keys.mp4 |
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| 043 Dictionary Keys-en_US.srt |
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| 043 Exercise_ Comprehensions.mp4 |
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| 043 Exercise_ Comprehensions-en_US.srt |
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| 043 Making Predictions On Our Images.mp4 |
119.42Мб |
| 043 Making Predictions On Our Images-en_US.srt |
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| 043 Tuning Hyperparameters.mp4 |
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| 043 Tuning Hyperparameters-en_US.srt |
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| 044 Dictionary Methods.mp4 |
10.08Мб |
| 044 Dictionary Methods-en_US.srt |
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| 044 Finishing Dog Vision_ Where to next_.html |
3.86Кб |
| 044 Python Exam_ Testing Your Understanding.html |
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| 044 Tuning Hyperparameters 2.mp4 |
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| 044 Tuning Hyperparameters 2-en_US.srt |
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| 045 Dictionary Methods 2.mp4 |
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| 045 Dictionary Methods 2-en_US.srt |
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| 045 Modules in Python.mp4 |
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| 045 Modules in Python-en_US.srt |
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| 045 Tuning Hyperparameters 3.mp4 |
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| 045 Tuning Hyperparameters 3-en_US.srt |
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| 046 Note_ Metric Comparison Improvement.html |
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| 046 Quick Note_ Upcoming Videos.html |
448б |
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