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Title [08-2020] python-data-science-machine-learning-bootcamp
Category
Size 23.25GB

Files List
Please note that this page does not hosts or makes available any of the listed filenames. You cannot download any of those files from here.
001 What is Machine Learning_.en_US.srt 6.41KB
001 What is Machine Learning_.mp4 32.37MB
002 What is Data Science_.en_US.srt 5.33KB
002 What is Data Science_.mp4 71.61MB
003 Download the Syllabus.html 2.14KB
003 ML-Data-Science-Syllabus.pdf 103.97KB
004 App-Brewery-Cornell-Notes-Template.txt 81B
004 Top Tips for Succeeding on this Course.html 2.72KB
005 Course Resources List.html 1.76KB
006 Course-Resources.txt 62B
006 Introduction to Linear Regression & Specifying the Problem.en_US.srt 8.08KB
006 Introduction to Linear Regression & Specifying the Problem.mp4 38.77MB
007 cost-revenue-dirty.csv 374.68KB
007 Gather & Clean the Data.en_US.srt 12.93KB
007 Gather & Clean the Data.mp4 69.03MB
007 The-Numbers-Movie-Budgets.txt 42B
008 cost-revenue-clean.csv 90.82KB
008 Explore & Visualise the Data with Python.en_US.srt 28.64KB
008 Explore & Visualise the Data with Python.mp4 188.77MB
008 Try-Jupyter-in-your-Browser.txt 25B
009 01-Linear-Regression-checkpoint.ipynb.zip 37.64KB
009 The Intuition behind the Linear Regression Model.en_US.srt 10.05KB
009 The Intuition behind the Linear Regression Model.mp4 19.46MB
010 Analyse and Evaluate the Results.en_US.srt 20.75KB
010 Analyse and Evaluate the Results.mp4 142.22MB
011 01-Linear-Regression-complete.ipynb.zip 75.28KB
011 Download the Complete Notebook Here.html 727B
012 Join the Student Community.html 1.34KB
013 Any Feedback on this Section_.html 997B
014 Course-Resources.txt 62B
014 Windows Users - Install Anaconda.en_US.srt 8.17KB
014 Windows Users - Install Anaconda.mp4 58.18MB
015 Course-Resources.txt 62B
015 Mac Users - Install Anaconda.en_US.srt 7.49KB
015 Mac Users - Install Anaconda.mp4 81.31MB
016 Does LSD Make You Better at Maths_.en_US.srt 6.82KB
016 Does LSD Make You Better at Maths_.mp4 66.90MB
017 12-Rules-to-Learn-to-Code.pdf 2.25MB
017 Download the 12 Rules to Learn to Code.html 1.77KB
018 [Python] - Variables and Types.en_US.srt 15.36KB
018 [Python] - Variables and Types.mp4 84.28MB
019 [exercise_info] Python Variable Coding Exercise.html 1.85KB
019 [exercise_solution] Python Variable Coding Exercise.zip 173B
019 [exercise] Python Variable Coding Exercise.zip 241B
019 [Python] - Lists and Arrays.en_US.srt 11.23KB
019 [Python] - Lists and Arrays.mp4 60.90MB
020 [exercise_info] Python Lists Coding Exercise.html 1.92KB
020 [exercise_solution] Python Lists Coding Exercise.zip 228B
020 [exercise] Python Lists Coding Exercise.zip 246B
020 [Python & Pandas] - Dataframes and Series.en_US.srt 25.94KB
020 [Python & Pandas] - Dataframes and Series.mp4 203.61MB
020 lsd-math-score-data.csv 155B
021 [Python] - Module Imports.en_US.srt 33.36KB
021 [Python] - Module Imports.mp4 349.51MB
022 [Python] - Functions - Part 1_ Defining and Calling Functions.en_US.srt 9.72KB
022 [Python] - Functions - Part 1_ Defining and Calling Functions.mp4 46.99MB
023 [exercise_info] Python Functions Coding Exercise - Part 1.html 1.64KB
023 [exercise_solution] Python Functions Coding Exercise - Part 1.zip 269B
023 [exercise] Python Functions Coding Exercise - Part 1.zip 285B
023 [Python] - Functions - Part 2_ Arguments & Parameters.en_US.srt 19.25KB
023 [Python] - Functions - Part 2_ Arguments & Parameters.mp4 189.68MB
024 [exercise_info] Python Functions Coding Exercise - Part 2.html 1.36KB
024 [exercise_solution] Python Functions Coding Exercise - Part 2.zip 253B
024 [exercise] Python Functions Coding Exercise - Part 2.zip 276B
024 [Python] - Functions - Part 3_ Results & Return Values.en_US.srt 15.34KB
024 [Python] - Functions - Part 3_ Results & Return Values.mp4 94.36MB
025 [exercise_info] Python Functions Coding Exercise - Part 3.html 1.42KB
025 [exercise_solution] Python Functions Coding Exercise - Part 3.zip 190B
025 [exercise] Python Functions Coding Exercise - Part 3.zip 210B
025 [Python] - Objects - Understanding Attributes and Methods.en_US.srt 27.54KB
025 [Python] - Objects - Understanding Attributes and Methods.mp4 234.49MB
026 How to Make Sense of Python Documentation for Data Visualisation.en_US.srt 24.48KB
026 How to Make Sense of Python Documentation for Data Visualisation.mp4 265.05MB
027 Working with Python Objects to Analyse Data.en_US.srt 25.09KB
027 Working with Python Objects to Analyse Data.mp4 258.83MB
028 [Python] - Tips, Code Style and Naming Conventions.en_US.srt 15.53KB
028 [Python] - Tips, Code Style and Naming Conventions.mp4 130.73MB
029 02-Python-Intro.ipynb.zip 36.44KB
029 Download the Complete Notebook Here.html 727B
030 Any Feedback on this Section_.html 998B
031 Course-Resources.txt 62B
031 What's Coming Up_.en_US.srt 3.56KB
031 What's Coming Up_.mp4 24.59MB
032 How a Machine Learns.en_US.srt 6.71KB
032 How a Machine Learns.mp4 16.56MB
033 Introduction to Cost Functions.en_US.srt 8.75KB
033 Introduction to Cost Functions.mp4 76.86MB
034 LaTeX Markdown and Generating Data with Numpy.en_US.srt 15.85KB
034 LaTeX Markdown and Generating Data with Numpy.mp4 77.24MB
035 Understanding the Power Rule & Creating Charts with Subplots.en_US.srt 16.63KB
035 Understanding the Power Rule & Creating Charts with Subplots.mp4 104.46MB
036 [Python] - Loops and the Gradient Descent Algorithm.en_US.srt 40.23KB
036 [Python] - Loops and the Gradient Descent Algorithm.mp4 449.20MB
037 [exercise_info] Python Loops Coding Exercise.html 15.48KB
037 [exercise_solution] Python Loops Coding Exercise.zip 288B
037 [exercise] Python Loops Coding Exercise.zip 260B
037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).en_US.srt 39.58KB
037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 446.84MB
038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).en_US.srt 30.87KB
038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 302.32MB
039 Understanding the Learning Rate.en_US.srt 34.67KB
039 Understanding the Learning Rate.mp4 280.53MB
040 How to Create 3-Dimensional Charts.en_US.srt 24.04KB
040 How to Create 3-Dimensional Charts.mp4 294.27MB
041 Understanding Partial Derivatives and How to use SymPy.en_US.srt 18.71KB
041 Understanding Partial Derivatives and How to use SymPy.mp4 193.33MB
042 Implementing Batch Gradient Descent with SymPy.en_US.srt 11.97KB
042 Implementing Batch Gradient Descent with SymPy.mp4 117.53MB
043 [Python] - Loops and Performance Considerations.en_US.srt 16.67KB
043 [Python] - Loops and Performance Considerations.mp4 205.61MB
044 Reshaping and Slicing N-Dimensional Arrays.en_US.srt 21.21KB
044 Reshaping and Slicing N-Dimensional Arrays.mp4 168.28MB
045 Concatenating Numpy Arrays.en_US.srt 8.28KB
045 Concatenating Numpy Arrays.mp4 85.15MB
046 Introduction to the Mean Squared Error (MSE).en_US.srt 11.70KB
046 Introduction to the Mean Squared Error (MSE).mp4 75.17MB
047 Transposing and Reshaping Arrays.en_US.srt 12.46KB
047 Transposing and Reshaping Arrays.mp4 101.68MB
048 Implementing a MSE Cost Function.en_US.srt 12.51KB
048 Implementing a MSE Cost Function.mp4 97.47MB
049 Understanding Nested Loops and Plotting the MSE Function (Part 1).en_US.srt 12.89KB
049 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 83.37MB
050 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).en_US.srt 16.01KB
050 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 68.86MB
051 Running Gradient Descent with a MSE Cost Function.en_US.srt 20.52KB
051 Running Gradient Descent with a MSE Cost Function.mp4 129.83MB
052 Visualising the Optimisation on a 3D Surface.en_US.srt 9.94KB
052 Visualising the Optimisation on a 3D Surface.mp4 88.19MB
053 03-Gradient-Descent.ipynb.zip 1.14MB
053 Download the Complete Notebook Here.html 727B
054 Any Feedback on this Section_.html 1005B
055 Course-Resources.txt 62B
055 Defining the Problem.en_US.srt 5.98KB
055 Defining the Problem.mp4 57.82MB
056 Gathering the Boston House Price Data.en_US.srt 8.03KB
056 Gathering the Boston House Price Data.mp4 91.05MB
057 Clean and Explore the Data (Part 1)_ Understand the Nature of the Dataset.en_US.srt 14.47KB
057 Clean and Explore the Data (Part 1)_ Understand the Nature of the Dataset.mp4 99.37MB
058 Clean and Explore the Data (Part 2)_ Find Missing Values.en_US.srt 17.24KB
058 Clean and Explore the Data (Part 2)_ Find Missing Values.mp4 207.91MB
059 Visualising Data (Part 1)_ Historams, Distributions & Outliers.en_US.srt 13.17KB
059 Visualising Data (Part 1)_ Historams, Distributions & Outliers.mp4 71.94MB
060 Visualising Data (Part 2)_ Seaborn and Probability Density Functions.en_US.srt 8.33KB
060 Visualising Data (Part 2)_ Seaborn and Probability Density Functions.mp4 66.18MB
061 Working with Index Data, Pandas Series, and Dummy Variables.en_US.srt 19.11KB
061 Working with Index Data, Pandas Series, and Dummy Variables.mp4 195.59MB
062 Understanding Descriptive Statistics_ the Mean vs the Median.en_US.srt 11.28KB
062 Understanding Descriptive Statistics_ the Mean vs the Median.mp4 72.50MB
063 Introduction to Correlation_ Understanding Strength & Direction.en_US.srt 7.81KB
063 Introduction to Correlation_ Understanding Strength & Direction.mp4 20.40MB
064 Calculating Correlations and the Problem posed by Multicollinearity.en_US.srt 16.46KB
064 Calculating Correlations and the Problem posed by Multicollinearity.mp4 154.88MB
065 Visualising Correlations with a Heatmap.en_US.srt 22.52KB
065 Visualising Correlations with a Heatmap.mp4 191.50MB
066 Techniques to Style Scatter Plots.en_US.srt 19.09KB
066 Techniques to Style Scatter Plots.mp4 149.97MB
067 A Note for the Next Lesson.html 961B
068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.en_US.srt 26.52KB
068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 334.45MB
069 Understanding Multivariable Regression.en_US.srt 6.98KB
069 Understanding Multivariable Regression.mp4 61.60MB
070 How to Shuffle and Split Training & Testing Data.en_US.srt 10.65KB
070 How to Shuffle and Split Training & Testing Data.mp4 83.32MB
071 Running a Multivariable Regression.en_US.srt 9.06KB
071 Running a Multivariable Regression.mp4 74.05MB
072 How to Calculate the Model Fit with R-Squared.en_US.srt 4.09KB
072 How to Calculate the Model Fit with R-Squared.mp4 38.56MB
073 Introduction to Model Evaluation.en_US.srt 3.53KB
073 Introduction to Model Evaluation.mp4 12.03MB
074 Improving the Model by Transforming the Data.en_US.srt 19.95KB
074 Improving the Model by Transforming the Data.mp4 142.49MB
075 How to Interpret Coefficients using p-Values and Statistical Significance.en_US.srt 10.04KB
075 How to Interpret Coefficients using p-Values and Statistical Significance.mp4 89.12MB
076 Understanding VIF & Testing for Multicollinearity.en_US.srt 23.67KB
076 Understanding VIF & Testing for Multicollinearity.mp4 164.60MB
077 Model Simplification & Baysian Information Criterion.en_US.srt 21.41KB
077 Model Simplification & Baysian Information Criterion.mp4 229.47MB
078 How to Analyse and Plot Regression Residuals.en_US.srt 13.66KB
078 How to Analyse and Plot Regression Residuals.mp4 46.63MB
079 Residual Analysis (Part 1)_ Predicted vs Actual Values.en_US.srt 16.78KB
079 Residual Analysis (Part 1)_ Predicted vs Actual Values.mp4 146.46MB
080 Residual Analysis (Part 2)_ Graphing and Comparing Regression Residuals.en_US.srt 20.96KB
080 Residual Analysis (Part 2)_ Graphing and Comparing Regression Residuals.mp4 178.21MB
081 Making Predictions (Part 1)_ MSE & R-Squared.en_US.srt 21.83KB
081 Making Predictions (Part 1)_ MSE & R-Squared.mp4 217.80MB
082 Making Predictions (Part 2)_ Standard Deviation, RMSE, and Prediction Intervals.en_US.srt 13.67KB
082 Making Predictions (Part 2)_ Standard Deviation, RMSE, and Prediction Intervals.mp4 116.49MB
083 Build a Valuation Tool (Part 1)_ Working with Pandas Series & Numpy ndarrays.en_US.srt 19.09KB
083 Build a Valuation Tool (Part 1)_ Working with Pandas Series & Numpy ndarrays.mp4 198.42MB
084 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).en_US.srt 19.66KB
084 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 159.88MB
085 [exercise_info] Python Conditional Statement Coding Exercise.html 2.54KB
085 [exercise_solution] Python Conditional Statement Coding Exercise.zip 200B
085 [exercise] Python Conditional Statement Coding Exercise.zip 167B
085 Build a Valuation Tool (Part 3)_ Docstrings & Creating your own Python Module.en_US.srt 26.12KB
085 Build a Valuation Tool (Part 3)_ Docstrings & Creating your own Python Module.mp4 167.92MB
086 04-Multivariable-Regression.ipynb.zip 3.54MB
086 04-Valuation-Tool.ipynb.zip 2.93KB
086 boston-valuation.py 3.05KB
086 Download the Complete Notebook Here.html 727B
087 Any Feedback on this Section_.html 997B
088 Course-Resources.txt 62B
088 How to Translate a Business Problem into a Machine Learning Problem.en_US.srt 8.99KB
088 How to Translate a Business Problem into a Machine Learning Problem.mp4 57.44MB
089 Gathering Email Data and Working with Archives & Text Editors.en_US.srt 13.05KB
089 Gathering Email Data and Working with Archives & Text Editors.mp4 186.87MB
089 SpamData.zip 21.28MB
090 How to Add the Lesson Resources to the Project.en_US.srt 4.55KB
090 How to Add the Lesson Resources to the Project.mp4 35.07MB
091 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.en_US.srt 5.67KB
091 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4 57.15MB
092 Basic Probability.en_US.srt 4.90KB
092 Basic Probability.mp4 15.52MB
093 Joint & Conditional Probability.en_US.srt 18.34KB
093 Joint & Conditional Probability.mp4 169.32MB
094 Bayes Theorem.en_US.srt 14.02KB
094 Bayes Theorem.mp4 94.54MB
095 Reading Files (Part 1)_ Absolute Paths and Relative Paths.en_US.srt 10.90KB
095 Reading Files (Part 1)_ Absolute Paths and Relative Paths.mp4 71.15MB
096 Reading Files (Part 2)_ Stream Objects and Email Structure.en_US.srt 13.52KB
096 Reading Files (Part 2)_ Stream Objects and Email Structure.mp4 167.33MB
097 Extracting the Text in the Email Body.en_US.srt 5.54KB
097 Extracting the Text in the Email Body.mp4 55.23MB
098 [Python] - Generator Functions & the yield Keyword.en_US.srt 20.66KB
098 [Python] - Generator Functions & the yield Keyword.mp4 197.71MB
099 Create a Pandas DataFrame of Email Bodies.en_US.srt 6.67KB
099 Create a Pandas DataFrame of Email Bodies.mp4 67.91MB
100 Cleaning Data (Part 1)_ Check for Empty Emails & Null Entries.en_US.srt 16.54KB
100 Cleaning Data (Part 1)_ Check for Empty Emails & Null Entries.mp4 191.89MB
101 Cleaning Data (Part 2)_ Working with a DataFrame Index.en_US.srt 8.50KB
101 Cleaning Data (Part 2)_ Working with a DataFrame Index.mp4 84.91MB
102 Saving a JSON File with Pandas.en_US.srt 6.45KB
102 Saving a JSON File with Pandas.mp4 81.28MB
103 Data Visualisation (Part 1)_ Pie Charts.en_US.srt 14.93KB
103 Data Visualisation (Part 1)_ Pie Charts.mp4 131.08MB
104 Data Visualisation (Part 2)_ Donut Charts.en_US.srt 8.85KB
104 Data Visualisation (Part 2)_ Donut Charts.mp4 73.40MB
105 Introduction to Natural Language Processing (NLP).en_US.srt 7.64KB
105 Introduction to Natural Language Processing (NLP).mp4 58.19MB
106 Tokenizing, Removing Stop Words and the Python Set Data Structure.en_US.srt 17.62KB
106 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4 138.05MB
107 Word Stemming & Removing Punctuation.en_US.srt 9.89KB
107 Word Stemming & Removing Punctuation.mp4 83.68MB
108 Removing HTML tags with BeautifulSoup.en_US.srt 10.28KB
108 Removing HTML tags with BeautifulSoup.mp4 167.47MB
109 Creating a Function for Text Processing.en_US.srt 8.04KB
109 Creating a Function for Text Processing.mp4 44.76MB
110 A Note for the Next Lesson.html 961B
111 Advanced Subsetting on DataFrames_ the apply() Function.en_US.srt 12.53KB
111 Advanced Subsetting on DataFrames_ the apply() Function.mp4 97.91MB
112 [Python] - Logical Operators to Create Subsets and Indices.en_US.srt 14.87KB
112 [Python] - Logical Operators to Create Subsets and Indices.mp4 101.30MB
113 Word Clouds & How to install Additional Python Packages.en_US.srt 11.12KB
113 Word Clouds & How to install Additional Python Packages.mp4 92.38MB
114 Creating your First Word Cloud.en_US.srt 12.72KB
114 Creating your First Word Cloud.mp4 152.62MB
115 Styling the Word Cloud with a Mask.en_US.srt 15.43KB
115 Styling the Word Cloud with a Mask.mp4 184.63MB
116 Solving the Hamlet Challenge.en_US.srt 5.55KB
116 Solving the Hamlet Challenge.mp4 92.62MB
117 Styling Word Clouds with Custom Fonts.en_US.srt 13.68KB
117 Styling Word Clouds with Custom Fonts.mp4 184.20MB
118 Create the Vocabulary for the Spam Classifier.en_US.srt 16.40KB
118 Create the Vocabulary for the Spam Classifier.mp4 124.04MB
119 Coding Challenge_ Check for Membership in a Collection.en_US.srt 5.64KB
119 Coding Challenge_ Check for Membership in a Collection.mp4 19.91MB
120 Coding Challenge_ Find the Longest Email.en_US.srt 6.97KB
120 Coding Challenge_ Find the Longest Email.mp4 76.59MB
121 Sparse Matrix (Part 1)_ Split the Training and Testing Data.en_US.srt 14.05KB
121 Sparse Matrix (Part 1)_ Split the Training and Testing Data.mp4 119.49MB
122 Sparse Matrix (Part 2)_ Data Munging with Nested Loops.en_US.srt 20.62KB
122 Sparse Matrix (Part 2)_ Data Munging with Nested Loops.mp4 160.46MB
123 Sparse Matrix (Part 3)_ Using groupby() and Saving .txt Files.en_US.srt 11.19KB
123 Sparse Matrix (Part 3)_ Using groupby() and Saving .txt Files.mp4 110.82MB
124 Coding Challenge Solution_ Preparing the Test Data.en_US.srt 4.18KB
124 Coding Challenge Solution_ Preparing the Test Data.mp4 37.54MB
125 Checkpoint_ Understanding the Data.en_US.srt 12.63KB
125 Checkpoint_ Understanding the Data.mp4 134.39MB
126 06-Bayes-Classifier-Pre-Processing.ipynb.zip 978.02KB
126 Download the Complete Notebook Here.html 727B
127 Any Feedback on this Section_.html 1004B
128 Course-Resources.txt 62B
128 Setting up the Notebook and Understanding Delimiters in a Dataset.en_US.srt 10.75KB
128 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4 99.17MB
128 SpamData.zip 22.31MB
129 Create a Full Matrix.en_US.srt 20.86KB
129 Create a Full Matrix.mp4 200.50MB
130 Count the Tokens to Train the Naive Bayes Model.en_US.srt 17.66KB
130 Count the Tokens to Train the Naive Bayes Model.mp4 111.37MB
131 Sum the Tokens across the Spam and Ham Subsets.en_US.srt 7.49KB
131 Sum the Tokens across the Spam and Ham Subsets.mp4 39.64MB
132 Calculate the Token Probabilities and Save the Trained Model.en_US.srt 9.07KB
132 Calculate the Token Probabilities and Save the Trained Model.mp4 70.53MB
133 Coding Challenge_ Prepare the Test Data.en_US.srt 4.95KB
133 Coding Challenge_ Prepare the Test Data.mp4 53.69MB
134 07-Bayes-Classifier-Training.ipynb.zip 5.82KB
134 Download the Complete Notebook Here.html 727B
135 Any Feedback on this Section_.html 1012B
136 Course-Resources.txt 62B
136 Set up the Testing Notebook.en_US.srt 3.67KB
136 Set up the Testing Notebook.mp4 36.94MB
136 SpamData.zip 22.83MB
137 Joint Conditional Probability (Part 1)_ Dot Product.en_US.srt 12.24KB
137 Joint Conditional Probability (Part 1)_ Dot Product.mp4 84.72MB
138 Joint Conditional Probablity (Part 2)_ Priors.en_US.srt 10.17KB
138 Joint Conditional Probablity (Part 2)_ Priors.mp4 90.70MB
139 Making Predictions_ Comparing Joint Probabilities.en_US.srt 9.31KB
139 Making Predictions_ Comparing Joint Probabilities.mp4 68.14MB
140 The Accuracy Metric.en_US.srt 7.35KB
140 The Accuracy Metric.mp4 46.42MB
141 Visualising the Decision Boundary.en_US.srt 32.20KB
141 Visualising the Decision Boundary.mp4 277.29MB
142 False Positive vs False Negatives.en_US.srt 12.32KB
142 False Positive vs False Negatives.mp4 71.62MB
143 The Recall Metric.en_US.srt 6.29KB
143 The Recall Metric.mp4 31.99MB
144 The Precision Metric.en_US.srt 9.13KB
144 The Precision Metric.mp4 61.48MB
145 The F-score or F1 Metric.en_US.srt 4.33KB
145 The F-score or F1 Metric.mp4 28.68MB
146 A Naive Bayes Implementation using SciKit Learn.en_US.srt 32.36KB
146 A Naive Bayes Implementation using SciKit Learn.mp4 270.52MB
147 07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip 243.05KB
147 08-Naive-Bayes-with-scikit-learn.ipynb.zip 13.26KB
147 Download the Complete Notebook Here.html 727B
148 Any Feedback on this Section_.html 994B
149 Course-Resources.txt 62B
149 The Human Brain and the Inspiration for Artificial Neural Networks.en_US.srt 10.48KB
149 The Human Brain and the Inspiration for Artificial Neural Networks.mp4 60.54MB
150 Layers, Feature Generation and Learning.en_US.srt 26.75KB
150 Layers, Feature Generation and Learning.mp4 237.20MB
151 Costs and Disadvantages of Neural Networks.en_US.srt 18.52KB
151 Costs and Disadvantages of Neural Networks.mp4 145.87MB
152 Preprocessing Image Data and How RGB Works.en_US.srt 15.54KB
152 Preprocessing Image Data and How RGB Works.mp4 129.57MB
152 TF-Keras-Classification-Images.zip 501.10KB
153 Importing Keras Models and the Tensorflow Graph.en_US.srt 11.03KB
153 Importing Keras Models and the Tensorflow Graph.mp4 73.36MB
154 Making Predictions using InceptionResNet.en_US.srt 18.18KB
154 Making Predictions using InceptionResNet.mp4 181.21MB
155 Coding Challenge Solution_ Using other Keras Models.en_US.srt 12.47KB
155 Coding Challenge Solution_ Using other Keras Models.mp4 154.95MB
156 09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip 571.83KB
156 Download the Complete Notebook Here.html 749B
157 Any Feedback on this Section_.html 1011B
158 Course-Resources.txt 62B
158 Solving a Business Problem with Image Classification.en_US.srt 4.79KB
158 Solving a Business Problem with Image Classification.mp4 37.55MB
159 Installing Tensorflow and Keras for Jupyter.en_US.srt 6.20KB
159 Installing Tensorflow and Keras for Jupyter.mp4 58.44MB
160 Gathering the CIFAR 10 Dataset.en_US.srt 5.88KB
160 Gathering the CIFAR 10 Dataset.mp4 35.34MB
161 Exploring the CIFAR Data.en_US.srt 17.51KB
161 Exploring the CIFAR Data.mp4 151.05MB
162 Pre-processing_ Scaling Inputs and Creating a Validation Dataset.en_US.srt 19.17KB
162 Pre-processing_ Scaling Inputs and Creating a Validation Dataset.mp4 103.65MB
163 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.en_US.srt 17.94KB
163 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4 139.62MB
164 Interacting with the Operating System and the Python Try-Catch Block.en_US.srt 22.83KB
164 Interacting with the Operating System and the Python Try-Catch Block.mp4 193.73MB
165 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.en_US.srt 13.57KB
165 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4 145.59MB
166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.en_US.srt 27.21KB
166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.mp4 287.09MB
167 Use the Model to Make Predictions.en_US.srt 31.77KB
167 Use the Model to Make Predictions.mp4 300.05MB
168 Model Evaluation and the Confusion Matrix.en_US.srt 10.37KB
168 Model Evaluation and the Confusion Matrix.mp4 81.83MB
169 Model Evaluation and the Confusion Matrix.en_US.srt 38.94KB
169 Model Evaluation and the Confusion Matrix.mp4 366.42MB
170 10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip 120.11KB
170 Download the Complete Notebook Here.html 727B
171 Any Feedback on this Section_.html 1006B
172 Course-Resources.txt 62B
172 What's coming up_.en_US.srt 2.40KB
172 What's coming up_.mp4 7.62MB
173 Getting the Data and Loading it into Numpy Arrays.en_US.srt 8.67KB
173 Getting the Data and Loading it into Numpy Arrays.mp4 75.07MB
173 MNIST.zip 14.77MB
174 Data Exploration and Understanding the Structure of the Input Data.en_US.srt 6.26KB
174 Data Exploration and Understanding the Structure of the Input Data.mp4 35.65MB
175 Data Preprocessing_ One-Hot Encoding and Creating the Validation Dataset.en_US.srt 12.20KB
175 Data Preprocessing_ One-Hot Encoding and Creating the Validation Dataset.mp4 88.53MB
176 What is a Tensor_.en_US.srt 8.66KB
176 What is a Tensor_.mp4 69.70MB
177 Creating Tensors and Setting up the Neural Network Architecture.en_US.srt 27.97KB
177 Creating Tensors and Setting up the Neural Network Architecture.mp4 205.12MB
178 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.en_US.srt 13.62KB
178 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4 84.85MB
179 TensorFlow Sessions and Batching Data.en_US.srt 19.71KB
179 TensorFlow Sessions and Batching Data.mp4 128.85MB
180 Tensorboard Summaries and the Filewriter.en_US.srt 22.36KB
180 Tensorboard Summaries and the Filewriter.mp4 186.50MB
181 Understanding the Tensorflow Graph_ Nodes and Edges.en_US.srt 20.45KB
181 Understanding the Tensorflow Graph_ Nodes and Edges.mp4 167.36MB
182 Name Scoping and Image Visualisation in Tensorboard.en_US.srt 25.29KB
182 Name Scoping and Image Visualisation in Tensorboard.mp4 88.68MB
183 Different Model Architectures_ Experimenting with Dropout.en_US.srt 29.00KB
183 Different Model Architectures_ Experimenting with Dropout.mp4 335.83MB
184 Prediction and Model Evaluation.en_US.srt 18.19KB
184 Prediction and Model Evaluation.mp4 162.28MB
185 11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6.60KB
185 Download the Complete Notebook Here.html 727B
186 Any Feedback on this Section_.html 984B
187 What you'll make.en_US.srt 9.39KB
187 What you'll make.mp4 64.36MB
188 11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6.39KB
188 Saving Tensorflow Models.en_US.srt 20.45KB
188 Saving Tensorflow Models.mp4 191.76MB
189 12-TF-SavedModel-Export-Completed.ipynb.zip 6.13KB
189 Loading a SavedModel.en_US.srt 25.16KB
189 Loading a SavedModel.mp4 144.86MB
189 MNIST-Model-Load-Files.zip 2.84MB
190 Converting a Model to Tensorflow.js.en_US.srt 20.34KB
190 Converting a Model to Tensorflow.js.mp4 171.61MB
190 TFJS.zip 1.54MB
191 Introducing the Website Project and Tooling.en_US.srt 16.60KB
191 Introducing the Website Project and Tooling.mp4 125.38MB
191 math-garden-stub.zip 44.03KB
192 HTML and CSS Styling.en_US.srt 36.48KB
192 HTML and CSS Styling.mp4 244.58MB
193 Loading a Tensorflow.js Model and Starting your own Server.en_US.srt 35.83KB
193 Loading a Tensorflow.js Model and Starting your own Server.mp4 321.34MB
193 x-test0-ylabel7.txt 4.59KB
193 x-test1-ylabel2.txt 4.59KB
193 x-test2-ylabel1.txt 4.59KB
194 Adding a Favicon.en_US.srt 7.11KB
194 Adding a Favicon.mp4 42.12MB
195 Styling an HTML Canvas.en_US.srt 37.97KB
195 Styling an HTML Canvas.mp4 312.41MB
196 Drawing on an HTML Canvas.en_US.srt 36.32KB
196 Drawing on an HTML Canvas.mp4 290.97MB
197 Data Pre-Processing for Tensorflow.js.en_US.srt 11.49KB
197 Data Pre-Processing for Tensorflow.js.mp4 42.36MB
198 Introduction to OpenCV.en_US.srt 36.93KB
198 Introduction to OpenCV.mp4 432.34MB
198 math-garden-stub-12.12-checkpoint.zip 4.09MB
199 Resizing and Adding Padding to Images.en_US.srt 25.81KB
199 Resizing and Adding Padding to Images.mp4 286.25MB
200 Calculating the Centre of Mass and Shifting the Image.en_US.srt 34.09KB
200 Calculating the Centre of Mass and Shifting the Image.mp4 405.91MB
201 Making a Prediction from a Digit drawn on the HTML Canvas.en_US.srt 16.40KB
201 Making a Prediction from a Digit drawn on the HTML Canvas.mp4 181.80MB
202 Adding the Game Logic.en_US.srt 36.55KB
202 Adding the Game Logic.mp4 286.00MB
202 math-garden-stub-complete.zip 4.09MB
203 Publish and Share your Website!.en_US.srt 9.14KB
203 Publish and Share your Website!.mp4 59.48MB
204 Any Feedback on this Section_.html 985B
205 Where next_.html 4.56KB
206 What Modules Do You Want to See_.html 916B
207 Stay in Touch!.html 1.52KB
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Russia (RU) 5
Turkey (TR) 2
Greece (GR) 1
Netherlands (NL) 1
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