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Please note that this page does not hosts or makes available any of the listed filenames. You
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| 01. 1.04.Real-life-example.csv |
219.83KB |
| 01. 2.13.Practical-example.Descriptive-statistics-lesson.xlsx |
146.51KB |
| 01. 3.17.Practical-example.Confidence-intervals-lesson.xlsx |
1.74MB |
| 01. 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf |
15.56MB |
| 01. 4.10.Hypothesis-testing-section-practical-example.xlsx |
51.90KB |
| 01. Absenteeism-data.csv |
32.05KB |
| 01. Absenteeism-Exercise-Integration.ipynb |
62.35KB |
| 01. absenteeism-module.py |
6.62KB |
| 01. Absenteeism-new-data.csv |
1.87KB |
| 01. Absenteeism-predictions.csv |
2.10KB |
| 01. Absenteeism-preprocessed.csv |
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| 01. Additional-Python-Tools-Exercises.ipynb |
11.41KB |
| 01. Additional-Python-Tools-Lectures.ipynb |
13.47KB |
| 01. Additional-Python-Tools-Solutions.ipynb |
25.52KB |
| 01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4 |
83.53MB |
| 01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt |
9.24KB |
| 01. A Practical Example What You Will Learn in This Course.mp4 |
10.76MB |
| 01. A Practical Example What You Will Learn in This Course.vtt |
6.82KB |
| 01. Are You Sure You're All Set.html |
519B |
| 01. Arithmetic-Operators-Exercise-Py3.ipynb |
2.62KB |
| 01. Arithmetic-Operators-Lecture-Py3.ipynb |
3.53KB |
| 01. Arithmetic-Operators-Solution-Py3.ipynb |
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| 01. Audiobooks-data.csv |
710.77KB |
| 01. Audiobooks-data.csv |
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| 01. Basic NN Example (Part 1).mp4 |
9.34MB |
| 01. Basic NN Example (Part 1).vtt |
4.54KB |
| 01. Bonus Lecture Next Steps.html |
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| 01. Business Case Exploring the Dataset and Identifying Predictors.mp4 |
51.29MB |
| 01. Business Case Exploring the Dataset and Identifying Predictors.vtt |
11.01KB |
| 01. Business Case Getting Acquainted with the Dataset.mp4 |
60.25MB |
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10.96KB |
| 01. Comparison Operators.mp4 |
4.16MB |
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| 01. Comparison-Operators-Exercise-Py3.ipynb |
1.61KB |
| 01. Comparison-Operators-Lecture-Py3.ipynb |
2.53KB |
| 01. Comparison-Operators-Solution-Py3.ipynb |
2.41KB |
| 01. Course-Notes-Basic-Probability.pdf |
371.05KB |
| 01. Course-Notes-Bayesian-Inference.pdf |
386.01KB |
| 01. Course-Notes-Cluster-Analysis.pdf |
208.65KB |
| 01. Course-Notes-Combinatorics.pdf |
226.12KB |
| 01. Course-notes-descriptive-statistics.pdf |
482.21KB |
| 01. Course-notes-descriptive-statistics.pdf |
482.21KB |
| 01. Course-notes-hypothesis-testing.pdf |
656.44KB |
| 01. Course-notes-inferential-statistics.pdf |
382.32KB |
| 01. Course-Notes-Logistic-Regression.pdf |
335.17KB |
| 01. Course-Notes-Probability-Distributions.pdf |
463.95KB |
| 01. Course-notes-regression-analysis.pdf |
312.18KB |
| 01. Course-notes-regression-analysis.pdf |
312.18KB |
| 01. Course-Notes-Section-2.pdf |
578.08KB |
| 01. Course-Notes-Section-6.pdf |
936.42KB |
| 01. data-preprocessing-homework.pdf |
134.47KB |
| 01. Data Science and Business Buzzwords Why are there so Many.mp4 |
15.59MB |
| 01. Data Science and Business Buzzwords Why are there so Many.vtt |
7.37KB |
| 01. Debunking Common Misconceptions.mp4 |
58.86MB |
| 01. Debunking Common Misconceptions.vtt |
5.53KB |
| 01. Defining a Function in Python.mp4 |
3.23MB |
| 01. Defining a Function in Python.vtt |
2.62KB |
| 01. Defining-a-Function-in-Python-Lecture-Py3.ipynb |
868B |
| 01. df-preprocessed.csv |
29.11KB |
| 01. EXERCISE - Age vs Probability.html |
385B |
| 01. Exploring the Problem with a Machine Learning Mindset.mp4 |
12.96MB |
| 01. Exploring the Problem with a Machine Learning Mindset.vtt |
4.83KB |
| 01. Finding the Job - What to Expect and What to Look for.mp4 |
40.03MB |
| 01. Finding the Job - What to Expect and What to Look for.vtt |
4.66KB |
| 01. For Loops.mp4 |
12.96MB |
| 01. For Loops.vtt |
6.77KB |
| 01. For-Loops-Exercise-Py3.ipynb |
1.28KB |
| 01. For-Loops-Lecture-Py3.ipynb |
1.26KB |
| 01. For-Loops-Solution-Py3.ipynb |
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| 01. Fundamentals of Combinatorics.mp4 |
5.94MB |
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1.47KB |
| 01. Fundamentals of Probability Distributions.mp4 |
19.42MB |
| 01. Fundamentals of Probability Distributions.vtt |
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| 01. Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 |
19.67MB |
| 01. Game Plan for this Python, SQL, and Tableau Business Exercise.vtt |
5.57KB |
| 01. Glossary.xlsx |
19.97KB |
| 01. How to Install TensorFlow 2.0.mp4 |
27.34MB |
| 01. How to Install TensorFlow 2.0.vtt |
6.57KB |
| 01. Introduction.mp4 |
3.06MB |
| 01. Introduction.vtt |
1.67KB |
| 01. Introduction to Cluster Analysis.mp4 |
14.46MB |
| 01. Introduction to Cluster Analysis.vtt |
4.96KB |
| 01. Introduction to Logistic Regression.mp4 |
5.87MB |
| 01. Introduction to Logistic Regression.vtt |
1.82KB |
| 01. Introduction to Neural Networks.mp4 |
10.49MB |
| 01. Introduction to Neural Networks.vtt |
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| 01. Introduction to pandas Series.mp4 |
24.96MB |
| 01. Introduction to pandas Series.vtt |
10.85KB |
| 01. Introduction to Programming.mp4 |
14.87MB |
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| 01. Introduction-to-Python-Course-Notes.pdf |
2.15MB |
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2.15MB |
| 01. Introduction to Regression Analysis.mp4 |
3.59MB |
| 01. Introduction to Regression Analysis.vtt |
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| 01. Introduction-to-the-If-Statement-Exercise-Py3.ipynb |
1.53KB |
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1.14KB |
| 01. Introduction-to-the-If-Statement-Solution-Py3.ipynb |
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| 01. Intro to the Case Study.mp4 |
10.42MB |
| 01. Intro to the Case Study.vtt |
3.74KB |
| 01. K-Means Clustering.mp4 |
10.82MB |
| 01. K-Means Clustering.vtt |
6.60KB |
| 01. Lending-company.csv |
112.43KB |
| 01. Lists.mp4 |
23.04MB |
| 01. Lists.vtt |
10.35KB |
| 01. Lists-Exercise-Py3.ipynb |
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2.70KB |
| 01. Lists-Solution-Py3.ipynb |
3.18KB |
| 01. Location.csv |
13.49KB |
| 01. Minimal-example-Part-1.ipynb |
1.19KB |
| 01. MNIST The Dataset.mp4 |
4.53MB |
| 01. MNIST The Dataset.vtt |
3.65KB |
| 01. MNIST What is the MNIST Dataset.mp4 |
4.80MB |
| 01. MNIST What is the MNIST Dataset.vtt |
3.60KB |
| 01. model |
1.01KB |
| 01. Multiple Linear Regression.mp4 |
5.68MB |
| 01. Multiple Linear Regression.vtt |
3.46KB |
| 01. Necessary Programming Languages and Software Used in Data Science.mp4 |
82.38MB |
| 01. Necessary Programming Languages and Software Used in Data Science.vtt |
7.97KB |
| 01. Null vs Alternative Hypothesis.mp4 |
31.94MB |
| 01. Null vs Alternative Hypothesis.vtt |
7.16KB |
| 01. Object Oriented Programming.mp4 |
8.66MB |
| 01. Object Oriented Programming.vtt |
6.86KB |
| 01. pandas-Fundamentals-Exercises.ipynb |
30.96KB |
| 01. pandas-Fundamentals-Lectures.ipynb |
21.31KB |
| 01. pandas-Fundamentals-Solutions.ipynb |
118.35KB |
| 01. Population and Sample.mp4 |
35.10MB |
| 01. Population and Sample.vtt |
5.84KB |
| 01. Practical Example Descriptive Statistics.mp4 |
130.53MB |
| 01. Practical Example Descriptive Statistics.vtt |
20.99KB |
| 01. Practical Example Hypothesis Testing.mp4 |
45.83MB |
| 01. Practical Example Hypothesis Testing.vtt |
8.62KB |
| 01. Practical Example Inferential Statistics.mp4 |
69.01MB |
| 01. Practical Example Inferential Statistics.vtt |
13.91KB |
| 01. Practical Example Linear Regression (Part 1).mp4 |
84.74MB |
| 01. Practical Example Linear Regression (Part 1).vtt |
14.86KB |
| 01. Preprocessing Introduction.mp4 |
9.23MB |
| 01. Preprocessing Introduction.vtt |
4.07KB |
| 01. Probability in Finance.mp4 |
40.35MB |
| 01. Probability in Finance.vtt |
10.08KB |
| 01. Probability-in-Finance-Homework.pdf |
110.68KB |
| 01. Probability-in-Finance-Solutions.pdf |
184.46KB |
| 01. READ ME!!!!.html |
564B |
| 01. Region.csv |
10.22KB |
| 01. Sales-products.csv |
152.28KB |
| 01. scaler |
1.86KB |
| 01. Sets and Events.mp4 |
17.67MB |
| 01. Sets and Events.vtt |
5.45KB |
| 01. Shortcuts-for-Jupyter.pdf |
619.17KB |
| 01. Shortcuts-for-Jupyter.pdf |
619.17KB |
| 01. sklearn-Linear-Regression-Practical-Example-Part-1.ipynb |
166.91KB |
| 01. sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb |
171.38KB |
| 01. Statistics-Glossary.xlsx |
20.26KB |
| 01. Stochastic Gradient Descent.mp4 |
7.83MB |
| 01. Stochastic Gradient Descent.vtt |
4.83KB |
| 01. Summary on What You've Learned.mp4 |
9.84MB |
| 01. Summary on What You've Learned.vtt |
5.48KB |
| 01. Techniques for Working with Traditional Data.mp4 |
107.18MB |
| 01. Techniques for Working with Traditional Data.vtt |
10.96KB |
| 01. The Basic Probability Formula.mp4 |
29.40MB |
| 01. The Basic Probability Formula.vtt |
8.96KB |
| 01. The IF Statement.mp4 |
6.71MB |
| 01. The IF Statement.vtt |
3.73KB |
| 01. The Linear Regression Model.mp4 |
13.48MB |
| 01. The Linear Regression Model.vtt |
8.13KB |
| 01. The Reason Behind These Disciplines.mp4 |
46.77MB |
| 01. The Reason Behind These Disciplines.vtt |
6.54KB |
| 01. Traditional data science methods and the role of ChatGPT.mp4 |
26.16MB |
| 01. Traditional data science methods and the role of ChatGPT.vtt |
7.20KB |
| 01. Types of Clustering.mp4 |
9.01MB |
| 01. Types of Clustering.vtt |
5.07KB |
| 01. Types of Data.mp4 |
43.19MB |
| 01. Types of Data.vtt |
5.82KB |
| 01. Using Arithmetic Operators in Python.mp4 |
8.63MB |
| 01. Using Arithmetic Operators in Python.vtt |
4.37KB |
| 01. Using the .format() Method.mp4 |
25.69MB |
| 01. Using the .format() Method.vtt |
12.66KB |
| 01. Variables.mp4 |
8.94MB |
| 01. Variables.vtt |
4.80KB |
| 01. Variables-Exercise-Py3.ipynb |
2.23KB |
| 01. Variables-Lecture-Py3.ipynb |
3.61KB |
| 01. Variables-Solution-Py3.ipynb |
3.79KB |
| 01. What are Confidence Intervals.mp4 |
28.61MB |
| 01. What are Confidence Intervals.vtt |
3.22KB |
| 01. What are Data, Servers, Clients, Requests, and Responses.mp4 |
19.51MB |
| 01. What are Data, Servers, Clients, Requests, and Responses.vtt |
6.29KB |
| 01. What is a Layer.mp4 |
5.17MB |
| 01. What is a Layer.vtt |
2.65KB |
| 01. What is a Matrix.mp4 |
11.94MB |
| 01. What is a Matrix.vtt |
4.63KB |
| 01. What is Initialization.mp4 |
8.90MB |
| 01. What is Initialization.vtt |
3.74KB |
| 01. What is Overfitting.mp4 |
10.81MB |
| 01. What is Overfitting.vtt |
5.87KB |
| 01. What is sklearn and How is it Different from Other Packages.mp4 |
8.48MB |
| 01. What is sklearn and How is it Different from Other Packages.vtt |
3.62KB |
| 01. What to Expect from the Following Sections.html |
2.48KB |
| 01. What to Expect from this Part.mp4 |
11.72MB |
| 01. What to Expect from this Part.vtt |
4.83KB |
| 02. 1.02.Multiple-linear-regression.csv |
1.09KB |
| 02. 1.04.Real-life-example.csv |
219.83KB |
| 02. 2.01.Admittance.csv |
1.58KB |
| 02. 2.13.Practical-example.Descriptive-statistics-exercise.xlsx |
120.27KB |
| 02. 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx |
146.38KB |
| 02. 3.01.Country-clusters.csv |
200B |
| 02. 3.17.Practical-example.Confidence-intervals-exercise.xlsx |
1.73MB |
| 02. 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx |
1.82MB |
| 02. 3.2.What-is-a-distribution-lesson.xlsx |
19.46KB |
| 02. 3.9.Population-variance-known-z-score-lesson.xlsx |
11.21KB |
| 02. 3.9.The-z-table.xlsx |
25.58KB |
| 02. 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx |
43.69KB |
| 02. 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx |
44.27KB |
| 02. Absenteeism-predictions.csv |
2.10KB |
| 02. Add-an-Else-Statement-Exercise-Py3.ipynb |
1.02KB |
| 02. Add-an-Else-Statement-Lecture-Py3.ipynb |
1.76KB |
| 02. Add-an-Else-Statement-Solution-Py3.ipynb |
1.40KB |
| 02. Adjusted R-Squared.mp4 |
34.20MB |
| 02. Adjusted R-Squared.vtt |
7.51KB |
| 02. Admittance.ipynb |
3.54KB |
| 02. Admittance-with-comments.ipynb |
5.32KB |
| 02. Analyzing Age vs Probability in Tableau.mp4 |
38.68MB |
| 02. Analyzing Age vs Probability in Tableau.vtt |
10.24KB |
| 02. A Note on Completing the Upcoming Coding Exercises.html |
2.96KB |
| 02. A Simple Example in Python.mp4 |
21.88MB |
| 02. A Simple Example in Python.vtt |
5.91KB |
| 02. A Simple Example of Clustering.mp4 |
34.18MB |
| 02. A Simple Example of Clustering.vtt |
9.74KB |
| 02. Basic NN Example (Part 2).mp4 |
15.23MB |
| 02. Basic NN Example (Part 2).vtt |
6.69KB |
| 02. Business Case Outlining the Solution.mp4 |
3.04MB |
| 02. Business Case Outlining the Solution.mp4 |
4.16MB |
| 02. Business Case Outlining the Solution.vtt |
1.91KB |
| 02. Business Case Outlining the Solution.vtt |
2.60KB |
| 02. Computing Expected Values.mp4 |
45.66MB |
| 02. Computing Expected Values.vtt |
6.95KB |
| 02. Confidence Intervals; Population Variance Known; Z-score.mp4 |
52.16MB |
| 02. Confidence Intervals; Population Variance Known; Z-score.vtt |
9.61KB |
| 02. Correlation vs Regression.mp4 |
3.84MB |
| 02. Correlation vs Regression.vtt |
2.16KB |
| 02. Country-clusters.ipynb |
3.31KB |
| 02. Country-clusters-with-comments.ipynb |
5.80KB |
| 02. Course-Notes-Cluster-Analysis.pdf |
208.65KB |
| 02. Course-notes-inferential-statistics.pdf |
382.32KB |
| 02. Course-Notes-Logistic-Regression.pdf |
335.17KB |
| 02. Course-Notes-Section-2.pdf |
578.08KB |
| 02. Course-Notes-Section-6.pdf |
936.42KB |
| 02. Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb |
1.16KB |
| 02. Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb |
1.59KB |
| 02. Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb |
1.79KB |
| 02. Creating the Targets for the Logistic Regression.mp4 |
32.44MB |
| 02. Creating the Targets for the Logistic Regression.vtt |
8.72KB |
| 02. Dendrogram.mp4 |
18.29MB |
| 02. Dendrogram.vtt |
7.58KB |
| 02. Deploying the 'absenteeism_module' - Part I.mp4 |
19.67MB |
| 02. Deploying the 'absenteeism_module' - Part I.vtt |
4.98KB |
| 02. Further Reading on Null and Alternative Hypothesis.html |
2.29KB |
| 02. Help-Yourself-with-Methods-Exercise-Py3.ipynb |
1.91KB |
| 02. Help-Yourself-with-Methods-Lecture-Py3.ipynb |
4.39KB |
| 02. Help-Yourself-with-Methods-Solution-Py3.ipynb |
2.83KB |
| 02. How are we Going to Approach this Section.mp4 |
5.30MB |
| 02. How are we Going to Approach this Section.vtt |
3.03KB |
| 02. How to Create a Function with a Parameter.mp4 |
9.99MB |
| 02. How to Create a Function with a Parameter.vtt |
4.52KB |
| 02. How to install ChatGPT.mp4 |
5.22MB |
| 02. How to install ChatGPT.vtt |
2.05KB |
| 02. How to Install TensorFlow 1.mp4 |
5.00MB |
| 02. How to Install TensorFlow 1.vtt |
3.40KB |
| 02. Importing the Absenteeism Data in Python.mp4 |
19.52MB |
| 02. Importing the Absenteeism Data in Python.vtt |
4.04KB |
| 02. Iterating Over Range Objects.mp4 |
12.61MB |
| 02. Iterating Over Range Objects.vtt |
6.43KB |
| 02. Levels of Measurement.mp4 |
32.19MB |
| 02. Levels of Measurement.vtt |
4.83KB |
| 02. Logical and Identity Operators.mp4 |
19.01MB |
| 02. Logical and Identity Operators.vtt |
5.97KB |
| 02. Logical-and-Identity-Operators-Lecture-Py3.ipynb |
5.86KB |
| 02. Logical-and-Identity-Operators-Solution-Py3.ipynb |
3.43KB |
| 02. Minimal-example-Part-2.ipynb |
3.65KB |
| 02. MNIST How to Tackle the MNIST.mp4 |
7.94MB |
| 02. MNIST How to Tackle the MNIST.mp4 |
8.01MB |
| 02. MNIST How to Tackle the MNIST.vtt |
3.63KB |
| 02. MNIST How to Tackle the MNIST.vtt |
3.84KB |
| 02. Modules and Packages.mp4 |
2.08MB |
| 02. Modules and Packages.vtt |
1.45KB |
| 02. Multiple-linear-regression-and-Adjusted-R-squared.ipynb |
2.15KB |
| 02. Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb |
2.80KB |
| 02. Numbers-and-Boolean-Values-Exercise-Py3.ipynb |
2.29KB |
| 02. Numbers and Boolean Values in Python.mp4 |
6.57MB |
| 02. Numbers and Boolean Values in Python.vtt |
3.75KB |
| 02. Numbers-and-Boolean-Values-Lecture-Py3.ipynb |
3.36KB |
| 02. Numbers-and-Boolean-Values-Solution-Py3.ipynb |
3.23KB |
| 02. Permutations and How to Use Them.mp4 |
17.52MB |
| 02. Permutations and How to Use Them.vtt |
4.41KB |
| 02. Practical Example Descriptive Statistics Exercise.html |
81B |
| 02. Practical Example Hypothesis Testing Exercise.html |
81B |
| 02. Practical Example Inferential Statistics Exercise.html |
81B |
| 02. Practical Example Linear Regression (Part 2).mp4 |
31.86MB |
| 02. Practical Example Linear Regression (Part 2).vtt |
8.33KB |
| 02. Probability in Statistics.mp4 |
31.60MB |
| 02. Probability in Statistics.vtt |
9.12KB |
| 02. Problems with Gradient Descent.mp4 |
3.65MB |
| 02. Problems with Gradient Descent.vtt |
2.99KB |
| 02. Real Life Examples of Traditional Data.mp4 |
18.37MB |
| 02. Real Life Examples of Traditional Data.vtt |
2.33KB |
| 02. Scalars and Vectors.mp4 |
8.54MB |
| 02. Scalars and Vectors.vtt |
4.01KB |
| 02. sklearn-Linear-Regression-Practical-Example-Part-2.ipynb |
328.74KB |
| 02. sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb |
335.63KB |
| 02. Some Examples of Clusters.mp4 |
35.86MB |
| 02. Some Examples of Clusters.vtt |
6.25KB |
| 02. TensorFlow Outline and Comparison with Other Libraries.mp4 |
15.29MB |
| 02. TensorFlow Outline and Comparison with Other Libraries.vtt |
5.49KB |
| 02. The Business Task.mp4 |
11.28MB |
| 02. The Business Task.vtt |
4.07KB |
| 02. The Double Equality Sign.mp4 |
2.72MB |
| 02. The Double Equality Sign.vtt |
1.90KB |
| 02. The-Double-Equality-Sign-Exercise-Py3.ipynb |
838B |
| 02. The-Double-Equality-Sign-Lecture-Py3.ipynb |
1.45KB |
| 02. The-Double-Equality-Sign-Solution-Py3.ipynb |
1.14KB |
| 02. The ELSE Statement.mp4 |
6.04MB |
| 02. The ELSE Statement.vtt |
3.25KB |
| 02. The Naive Bayes Algorithm.mp4 |
42.06MB |
| 02. The Naive Bayes Algorithm.vtt |
6.08KB |
| 02. Training the Model.mp4 |
7.72MB |
| 02. Training the Model.vtt |
4.74KB |
| 02. Types of Basic Preprocessing.mp4 |
3.25MB |
| 02. Types of Basic Preprocessing.vtt |
1.85KB |
| 02. Types of Probability Distributions.mp4 |
35.59MB |
| 02. Types of Probability Distributions.vtt |
10.44KB |
| 02. Types of Simple Initializations.mp4 |
5.73MB |
| 02. Types of Simple Initializations.vtt |
3.78KB |
| 02. Underfitting and Overfitting for Classification.mp4 |
14.01MB |
| 02. Underfitting and Overfitting for Classification.vtt |
2.83KB |
| 02. Using Methods.mp4 |
30.36MB |
| 02. Using Methods.vtt |
8.72KB |
| 02. Ways Sets Can Interact.mp4 |
11.33MB |
| 02. Ways Sets Can Interact.vtt |
4.62KB |
| 02. What's Further out there in terms of Machine Learning.mp4 |
4.79MB |
| 02. What's Further out there in terms of Machine Learning.vtt |
2.70KB |
| 02. What are Data Connectivity, APIs, and Endpoints.mp4 |
60.22MB |
| 02. What are Data Connectivity, APIs, and Endpoints.vtt |
9.17KB |
| 02. What Does the Course Cover.mp4 |
9.56MB |
| 02. What Does the Course Cover.vtt |
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29.60MB |
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15.79MB |
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| 05. Mutually Exclusive Sets.mp4 |
10.58MB |
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17.70MB |
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| 05. OLS Assumptions.mp4 |
5.26MB |
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14.59MB |
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21.13MB |
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16.00MB |
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| 05. Solving Variations without Repetition.mp4 |
18.25MB |
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36.06MB |
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| 05. Student's T Distribution.mp4 |
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36.94MB |
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| 05. The Linear Model with Multiple Inputs.mp4 |
7.91MB |
| 05. The Linear Model with Multiple Inputs.vtt |
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| 05. The Standard Normal Distribution Exercise.html |
81B |
| 05. Traditional AI vs. Generative AI.mp4 |
24.51MB |
| 05. Traditional AI vs. Generative AI.vtt |
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| 05. Types of File Formats Supporting TensorFlow.mp4 |
8.86MB |
| 05. Types of File Formats Supporting TensorFlow.vtt |
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| 05. Understanding Jupyter's Interface - the Notebook Dashboard.mp4 |
6.07MB |
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| 05. Understanding Line Continuation.mp4 |
1.20MB |
| 05. Understanding Line Continuation.vtt |
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| 05. What's Regression Analysis - a Quick Refresher.html |
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| 05. What is a Tensor.mp4 |
15.54MB |
| 05. What is a Tensor.vtt |
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| 06. 12.6.TensorFlow-MNIST-with-comments-Part-4.ipynb |
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| 06. 2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx |
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| 06. 3.11.Population-variance-unknown-t-score-lesson.xlsx |
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| 06. 5.3.TensorFlow-Minimal-example-Part-1.ipynb |
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| 06. A1 Linearity.mp4 |
3.57MB |
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| 06. Activation Functions Softmax Activation.mp4 |
8.74MB |
| 06. Activation Functions Softmax Activation.vtt |
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| 06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4 |
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22.10MB |
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| 06. Analyzing a client database with ChatGPT in Python.mp4 |
21.62MB |
| 06. Analyzing a client database with ChatGPT in Python.vtt |
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| 06. Analyzing Transportation Expense vs Probability in Tableau.mp4 |
16.48MB |
| 06. Analyzing Transportation Expense vs Probability in Tableau.vtt |
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| 06. An Invaluable Coding Tip.mp4 |
18.78MB |
| 06. An Invaluable Coding Tip.vtt |
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| 06. Anonymous (Lambda) Functions.mp4 |
22.78MB |
| 06. Anonymous (Lambda) Functions.vtt |
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| 06. An Overview of non-NN Approaches.mp4 |
16.08MB |
| 06. An Overview of non-NN Approaches.vtt |
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| 06. Business Case Load the Preprocessed Data.mp4 |
13.81MB |
| 06. Business Case Load the Preprocessed Data.vtt |
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| 06. Calculating the Accuracy of the Model.mp4 |
24.45MB |
| 06. Calculating the Accuracy of the Model.vtt |
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| 06. Central Limit Theorem.mp4 |
23.22MB |
| 06. Central Limit Theorem.vtt |
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| 06. Combinations-With-Repetition.pdf |
207.41KB |
| 06. Confidence Intervals; Population Variance Unknown; T-score.mp4 |
13.69MB |
| 06. Confidence Intervals; Population Variance Unknown; T-score.vtt |
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| 06. Creating a Data Provider.mp4 |
56.30MB |
| 06. Creating a Data Provider.vtt |
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| 06. Creating-Functions-Containing-a-Few-Arguments-Lecture-Py3.ipynb |
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| 06. customers.csv |
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| 06. Dependence and Independence of Sets.mp4 |
14.92MB |
| 06. Dependence and Independence of Sets.vtt |
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| 06. Discrete Distributions The Binomial Distribution.mp4 |
30.60MB |
| 06. Discrete Distributions The Binomial Distribution.vtt |
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| 06. Early Stopping or When to Stop Training.mp4 |
10.29MB |
| 06. Early Stopping or When to Stop Training.vtt |
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| 06. First Regression in Python Exercise.html |
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| 06. Fitting the Model and Assessing its Accuracy.mp4 |
15.22MB |
| 06. Fitting the Model and Assessing its Accuracy.vtt |
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| 06. Functions Containing a Few Arguments.mp4 |
2.81MB |
| 06. Functions Containing a Few Arguments.vtt |
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| 06. How to Choose the Number of Clusters.mp4 |
26.87MB |
| 06. How to Choose the Number of Clusters.vtt |
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| 06. How to Iterate over Dictionaries.mp4 |
18.38MB |
| 06. How to Iterate over Dictionaries.vtt |
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| 06. Indexing Elements.mp4 |
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32.69MB |
| 06. MNIST Preprocess the Data - Shuffle and Batch.vtt |
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| 06. More Examples of Generative AI.mp4 |
30.54MB |
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26.96MB |
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| 06. Practical Example Linear Regression (Part 4).mp4 |
39.39MB |
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| 06. Prerequisites for Coding in the Jupyter Notebooks.mp4 |
18.96MB |
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24.62MB |
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| 06. Solving Combinations.mp4 |
23.64MB |
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6.03KB |
| 06. TensorFlow-Minimal-example-Part2.ipynb |
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| 06. Test for the Mean. Population Variance Known Exercise.html |
81B |
| 06. The Linear model with Multiple Inputs and Multiple Outputs.mp4 |
16.64MB |
| 06. The Linear model with Multiple Inputs and Multiple Outputs.vtt |
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8.90MB |
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24.31MB |
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9.90MB |
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9.24MB |
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| 07. A Breakdown of our Data Science Infographic.mp4 |
45.37MB |
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| 07. Adam (Adaptive Moment Estimation).mp4 |
7.14MB |
| 07. Adam (Adaptive Moment Estimation).vtt |
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| 07. Analyzing a client database with ChatGPT in Python – analyzing top products.mp4 |
15.17MB |
| 07. Analyzing a client database with ChatGPT in Python – analyzing top products.vtt |
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| 07. Backpropagation.mp4 |
20.34MB |
| 07. Backpropagation.vtt |
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| 07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4 |
17.69MB |
| 07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.vtt |
7.97KB |
| 07. Built-in Functions in Python.mp4 |
10.19MB |
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| 07. Business Case Load the Preprocessed Data - Exercise.html |
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42.51MB |
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| 07. Confidence Intervals; Population Variance Unknown; T-score; Exercise.html |
81B |
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26.95MB |
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| 07. Discrete Distributions The Poisson Distribution.mp4 |
23.92MB |
| 07. Discrete Distributions The Poisson Distribution.vtt |
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| 07. Dropping a Column from a DataFrame in Python.mp4 |
41.24MB |
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5.77MB |
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| 07. Graphical Representation of Simple Neural Networks.mp4 |
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25.91MB |
| 07. Interpreting the Result and Extracting the Weights and Bias.vtt |
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18.67MB |
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13.74MB |
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76.01MB |
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20.07MB |
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9.58MB |
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14.59MB |
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13.61MB |
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29.40MB |
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26.94MB |
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16.90MB |
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| 08. Customizing a TensorFlow 2 Model.mp4 |
16.76MB |
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| 08. Estimators and Estimates.mp4 |
27.69MB |
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| 08. Histogram Exercise.html |
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28.73MB |
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| 08. Interpreting the Coefficients for Our Problem.mp4 |
41.14MB |
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12.46MB |
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| 08. Margin of Error.mp4 |
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50.42MB |
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11.12MB |
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36.74MB |
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16.18MB |
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| 08. Solving Combinations with Separate Sample Spaces.mp4 |
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16.83MB |
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32.21MB |
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| 13. Calculating-the-Accuracy-of-the-Model-Solution.ipynb |
81.21KB |
| 13. Confidence intervals. Two means. Independent Samples (Part 2).mp4 |
14.62MB |
| 13. Confidence intervals. Two means. Independent Samples (Part 2).vtt |
4.69KB |
| 13. Continuous Distributions The Exponential Distribution.mp4 |
15.99MB |
| 13. Continuous Distributions The Exponential Distribution.vtt |
4.47KB |
| 13. How is Clustering Useful.mp4 |
37.43MB |
| 13. How is Clustering Useful.vtt |
6.78KB |
| 13. Lending-company.csv |
112.43KB |
| 13. Location.csv |
13.49KB |
| 13. Making-predictions.ipynb |
5.77KB |
| 13. Making-predictions-with-comments.ipynb |
9.41KB |
| 13. Making Predictions with the Linear Regression.mp4 |
16.34MB |
| 13. Making Predictions with the Linear Regression.vtt |
4.44KB |
| 13. Marvels comic book database Intro to Regular Expressions (RegEx).mp4 |
14.98MB |
| 13. Marvels comic book database Intro to Regular Expressions (RegEx).vtt |
2.72KB |
| 13. Multiple Linear Regression - Exercise.html |
76B |
| 13. pandas DataFrames - Indexing with .loc[].mp4 |
20.69MB |
| 13. pandas DataFrames - Indexing with .loc[].vtt |
5.56KB |
| 13. pandas-Fundamentals-Exercises.ipynb |
30.96KB |
| 13. pandas-Fundamentals-Lectures.ipynb |
21.31KB |
| 13. pandas-Fundamentals-Solutions.ipynb |
118.35KB |
| 13. real-estate-price-size-year.csv |
2.35KB |
| 13. Region.csv |
10.22KB |
| 13. Sales-products.csv |
152.28KB |
| 13. Saving the Model and Preparing it for Deployment.mp4 |
25.52MB |
| 13. Saving the Model and Preparing it for Deployment.vtt |
5.76KB |
| 13. Skewness.mp4 |
13.32MB |
| 13. Skewness.vtt |
3.73KB |
| 13. sklearn-Multiple-Linear-Regression-Exercise.ipynb |
5.67KB |
| 13. sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb |
15.44KB |
| 13. SOLUTION - Obtaining Dummies from a Single Feature.html |
117B |
| 13. Test for the mean. Independent Samples (Part 1). Exercise.html |
81B |
| 14. 1.02.Multiple-linear-regression.csv |
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| 14. 2.8.Skewness-exercise.xlsx |
9.49KB |
| 14. 2.8.Skewness-exercise-solution.xlsx |
19.78KB |
| 14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx |
9.17KB |
| 14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx |
9.79KB |
| 14. 4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx |
9.31KB |
| 14. ARTICLE - A Note on 'pickling'.html |
2.14KB |
| 14. Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html |
81B |
| 14. Continuous Distributions The Logistic Distribution.mp4 |
16.18MB |
| 14. Continuous Distributions The Logistic Distribution.vtt |
5.41KB |
| 14. Decoding comic book data Python Regular Expressions and ChatGPT.mp4 |
33.05MB |
| 14. Decoding comic book data Python Regular Expressions and ChatGPT.vtt |
6.45KB |
| 14. Dropping a Dummy Variable from the Data Set.html |
2.34KB |
| 14. EXERCISE Species Segmentation with Cluster Analysis (Part 1).html |
87B |
| 14. Feature Scaling (Standardization).mp4 |
20.37MB |
| 14. Feature Scaling (Standardization).vtt |
8.78KB |
| 14. iris-dataset.csv |
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| 14. Marvel-Comics-Reg-Ex.ipynb |
29.49KB |
| 14. Skewness Exercise.html |
81B |
| 14. SKLEAR-1.IPY |
12.87KB |
| 14. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb |
11.73KB |
| 14. Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb |
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| 14. Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb |
7.35KB |
| 14. Test for the mean. Independent Samples (Part 2).mp4 |
24.45MB |
| 14. Test for the mean. Independent Samples (Part 2).vtt |
5.39KB |
| 14. Underfitting and Overfitting.mp4 |
7.49MB |
| 14. Underfitting and Overfitting.vtt |
5.16KB |
| 15. 1.02.Multiple-linear-regression.csv |
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| 15. 2.03.Test-dataset.csv |
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| 15. 2.9.Variance-lesson.xlsx |
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| 15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx |
10.54KB |
| 15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx |
11.39KB |
| 15. A Practical Example of Probability Distributions.mp4 |
138.31MB |
| 15. A Practical Example of Probability Distributions.vtt |
21.13KB |
| 15. Assignment 2.html |
1.56KB |
| 15. Confidence intervals. Two means. Independent Samples (Part 3).mp4 |
6.88MB |
| 15. Confidence intervals. Two means. Independent Samples (Part 3).vtt |
2.03KB |
| 15. Customers-Membership.xlsx |
9.69KB |
| 15. Customers-Membership-post.xlsx |
15.62KB |
| 15. Daily-Views.xlsx |
9.53KB |
| 15. Daily-Views-post.xlsx |
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| 15. EXERCISE - Saving the Model (and Scaler).html |
284B |
| 15. EXERCISE Species Segmentation with Cluster Analysis (Part 2).html |
87B |
| 15. Feature Selection through Standardization of Weights.mp4 |
24.46MB |
| 15. Feature Selection through Standardization of Weights.vtt |
7.62KB |
| 15. FIFA19.csv |
8.64MB |
| 15. FIFA19-post.csv |
8.64MB |
| 15. iris-dataset.csv |
2.40KB |
| 15. iris-with-answers.csv |
3.63KB |
| 15. More on Dummy Variables A Statistical Perspective.mp4 |
5.82MB |
| 15. More on Dummy Variables A Statistical Perspective.vtt |
1.71KB |
| 15. SKLEAR-1.IPY |
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| 15. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb |
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| 15. Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb |
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| 15. Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb |
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| 15. Test for the mean. Independent Samples (Part 2). Exercise.html |
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| 15. Testing-the-model.ipynb |
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| 15. Testing the Model.mp4 |
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| 15. Testing the Model.vtt |
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| 15. Testing-the-model-with-comments.ipynb |
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| 15. Variance.mp4 |
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| 15. Variance.vtt |
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| 16. 1.02.Multiple-linear-regression.csv |
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| 16. 2.9.Variance-exercise.xlsx |
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| 16. 2.9.Variance-exercise-solution.xlsx |
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| 16. Algorithm recommendation Movie Database Analysis with ChatGPT.mp4 |
17.25MB |
| 16. Algorithm recommendation Movie Database Analysis with ChatGPT.vtt |
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| 16. Bank-data.csv |
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| 16. Bank-data-testing.csv |
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| 16. Classifying the Various Reasons for Absence.mp4 |
51.32MB |
| 16. Classifying the Various Reasons for Absence.vtt |
10.52KB |
| 16. Predicting with the Standardized Coefficients.mp4 |
20.44MB |
| 16. Predicting with the Standardized Coefficients.vtt |
5.55KB |
| 16. Preparing the Deployment of the Model through a Module.mp4 |
28.56MB |
| 16. Preparing the Deployment of the Model through a Module.vtt |
5.90KB |
| 16. ratings-small.csv |
2.33MB |
| 16. sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb |
29.75KB |
| 16. sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb |
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| 16. Testing the Model - Exercise.html |
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| 16. Testing-the-Model-Exercise.ipynb |
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| 16. Testing-the-Model-Solution.ipynb |
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| 16. Variance Exercise.html |
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| 17. 2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx |
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| 17. Algorithm recommendation recommendation engine for movies with ChatGPT.mp4 |
17.85MB |
| 17. Algorithm recommendation recommendation engine for movies with ChatGPT.vtt |
6.36KB |
| 17. Feature Scaling (Standardization) - Exercise.html |
76B |
| 17. Movies-Data-Base-Recommendation-Engine.ipynb |
20.39KB |
| 17. real-estate-price-size-year.csv |
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| 17. sklearn-Feature-Scaling-Exercise.ipynb |
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| 17. sklearn-Feature-Scaling-Exercise-Solution.ipynb |
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| 17. Standard Deviation and Coefficient of Variation.mp4 |
20.12MB |
| 17. Standard Deviation and Coefficient of Variation.vtt |
6.35KB |
| 17. Using .concat() in Python.mp4 |
27.34MB |
| 17. Using .concat() in Python.vtt |
5.17KB |
| 18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx |
11.61KB |
| 18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx |
12.60KB |
| 18. Ethical principles in data and AI utilization.mp4 |
14.73MB |
| 18. Ethical principles in data and AI utilization.vtt |
4.36KB |
| 18. EXERCISE - Using .concat() in Python.html |
189B |
| 18. Standard Deviation and Coefficient of Variation Exercise.html |
81B |
| 18. Underfitting and Overfitting.mp4 |
5.83MB |
| 18. Underfitting and Overfitting.vtt |
3.75KB |
| 19. 2.11.Covariance-lesson.xlsx |
24.92KB |
| 19. Covariance.mp4 |
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| 19. Covariance.vtt |
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| 19. friendships.csv |
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| 19. interactions.csv |
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| 19. posts.csv |
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| 19. sklearn-Train-Test-Split.ipynb |
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| 19. sklearn-Train-Test-Split-with-comments.ipynb |
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| 19. SOLUTION - Using .concat() in Python.html |
143B |
| 19. Train - Test Split Explained.mp4 |
35.57MB |
| 19. Train - Test Split Explained.vtt |
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| 19. users.csv |
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| 19. Using ChatGPT for ethical considerations.mp4 |
33.53MB |
| 19. Using ChatGPT for ethical considerations.vtt |
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| 20. 2.11.Covariance-exercise.xlsx |
20.23KB |
| 20. 2.11.Covariance-exercise-solution.xlsx |
29.51KB |
| 20. Covariance Exercise.html |
81B |
| 20. Reordering Columns in a Pandas DataFrame in Python.mp4 |
10.00MB |
| 20. Reordering Columns in a Pandas DataFrame in Python.vtt |
1.87KB |
| 21. Correlation Coefficient.mp4 |
19.32MB |
| 21. Correlation Coefficient.vtt |
4.96KB |
| 21. EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html |
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| 22. 2.12.Correlation-exercise.xlsx |
29.30KB |
| 22. 2.12.Correlation-exercise-solution.xlsx |
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| 22. Correlation Coefficient Exercise.html |
81B |
| 22. SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html |
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| 23. Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb |
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| 23. Creating Checkpoints while Coding in Jupyter.mp4 |
17.33MB |
| 23. Creating Checkpoints while Coding in Jupyter.vtt |
3.67KB |
| 24. EXERCISE - Creating Checkpoints while Coding in Jupyter.html |
137B |
| 25. SOLUTION - Creating Checkpoints while Coding in Jupyter.html |
118B |
| 26. Analyzing the Dates from the Initial Data Set.mp4 |
40.12MB |
| 26. Analyzing the Dates from the Initial Data Set.vtt |
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| 27. Extracting the Month Value from the Date Column.mp4 |
33.90MB |
| 27. Extracting the Month Value from the Date Column.vtt |
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| 28. Extracting the Day of the Week from the Date Column.mp4 |
19.14MB |
| 28. Extracting the Day of the Week from the Date Column.vtt |
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| 29. Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb |
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| 29. Absenteeism-Exercise-Preprocessing-LECTURES.ipynb |
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| 29. Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb |
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| 29. EXERCISE - Removing the Date Column.html |
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| 30. Analyzing Several Straightforward Columns for this Exercise.mp4 |
14.32MB |
| 30. Analyzing Several Straightforward Columns for this Exercise.vtt |
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| 31. Working on Education, Children, and Pets.mp4 |
27.03MB |
| 31. Working on Education, Children, and Pets.vtt |
5.96KB |
| 32. Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb |
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| 32. Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb |
8.51KB |
| 32. Final Remarks of this Section.mp4 |
13.54MB |
| 32. Final Remarks of this Section.vtt |
2.68KB |
| 33. A Note on Exporting Your Data as a .csv File.html |
883B |
| Marvel_Comics.csv |
12.99MB |
| movies_metadata.csv |
32.85MB |