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| 01. 1.04.Real-life-example.csv |
219.83Кб |
| 01. 2.13.Practical-example.Descriptive-statistics-lesson.xlsx |
146.51Кб |
| 01. 3.17.Practical-example.Confidence-intervals-lesson.xlsx |
1.74Мб |
| 01. 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf |
15.56Мб |
| 01. 4.10.Hypothesis-testing-section-practical-example.xlsx |
51.90Кб |
| 01. Absenteeism-data.csv |
32.05Кб |
| 01. Absenteeism-Exercise-Integration.ipynb |
62.35Кб |
| 01. absenteeism-module.py |
6.62Кб |
| 01. Absenteeism-new-data.csv |
1.87Кб |
| 01. Absenteeism-predictions.csv |
2.10Кб |
| 01. Absenteeism-preprocessed.csv |
29.13Кб |
| 01. Additional-Python-Tools-Exercises.ipynb |
11.41Кб |
| 01. Additional-Python-Tools-Lectures.ipynb |
13.47Кб |
| 01. Additional-Python-Tools-Solutions.ipynb |
25.52Кб |
| 01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4 |
83.53Мб |
| 01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt |
9.24Кб |
| 01. A Practical Example What You Will Learn in This Course.mp4 |
10.76Мб |
| 01. A Practical Example What You Will Learn in This Course.vtt |
6.82Кб |
| 01. Are You Sure You're All Set.html |
519б |
| 01. Arithmetic-Operators-Exercise-Py3.ipynb |
2.62Кб |
| 01. Arithmetic-Operators-Lecture-Py3.ipynb |
3.53Кб |
| 01. Arithmetic-Operators-Solution-Py3.ipynb |
4.24Кб |
| 01. Audiobooks-data.csv |
710.77Кб |
| 01. Audiobooks-data.csv |
710.77Кб |
| 01. Basic NN Example (Part 1).mp4 |
9.34Мб |
| 01. Basic NN Example (Part 1).vtt |
4.54Кб |
| 01. Bonus Lecture Next Steps.html |
4.33Кб |
| 01. Business Case Exploring the Dataset and Identifying Predictors.mp4 |
51.29Мб |
| 01. Business Case Exploring the Dataset and Identifying Predictors.vtt |
11.01Кб |
| 01. Business Case Getting Acquainted with the Dataset.mp4 |
60.25Мб |
| 01. Business Case Getting Acquainted with the Dataset.vtt |
10.96Кб |
| 01. Comparison Operators.mp4 |
4.16Мб |
| 01. Comparison Operators.vtt |
2.57Кб |
| 01. Comparison-Operators-Exercise-Py3.ipynb |
1.61Кб |
| 01. Comparison-Operators-Lecture-Py3.ipynb |
2.53Кб |
| 01. Comparison-Operators-Solution-Py3.ipynb |
2.41Кб |
| 01. Course-Notes-Basic-Probability.pdf |
371.05Кб |
| 01. Course-Notes-Bayesian-Inference.pdf |
386.01Кб |
| 01. Course-Notes-Cluster-Analysis.pdf |
208.65Кб |
| 01. Course-Notes-Combinatorics.pdf |
226.12Кб |
| 01. Course-notes-descriptive-statistics.pdf |
482.21Кб |
| 01. Course-notes-descriptive-statistics.pdf |
482.21Кб |
| 01. Course-notes-hypothesis-testing.pdf |
656.44Кб |
| 01. Course-notes-inferential-statistics.pdf |
382.32Кб |
| 01. Course-Notes-Logistic-Regression.pdf |
335.17Кб |
| 01. Course-Notes-Probability-Distributions.pdf |
463.95Кб |
| 01. Course-notes-regression-analysis.pdf |
312.18Кб |
| 01. Course-notes-regression-analysis.pdf |
312.18Кб |
| 01. Course-Notes-Section-2.pdf |
578.08Кб |
| 01. Course-Notes-Section-6.pdf |
936.42Кб |
| 01. data-preprocessing-homework.pdf |
134.47Кб |
| 01. Data Science and Business Buzzwords Why are there so Many.mp4 |
15.59Мб |
| 01. Data Science and Business Buzzwords Why are there so Many.vtt |
7.37Кб |
| 01. Debunking Common Misconceptions.mp4 |
58.86Мб |
| 01. Debunking Common Misconceptions.vtt |
5.53Кб |
| 01. Defining a Function in Python.mp4 |
3.23Мб |
| 01. Defining a Function in Python.vtt |
2.62Кб |
| 01. Defining-a-Function-in-Python-Lecture-Py3.ipynb |
868б |
| 01. df-preprocessed.csv |
29.11Кб |
| 01. EXERCISE - Age vs Probability.html |
385б |
| 01. Exploring the Problem with a Machine Learning Mindset.mp4 |
12.96Мб |
| 01. Exploring the Problem with a Machine Learning Mindset.vtt |
4.83Кб |
| 01. Finding the Job - What to Expect and What to Look for.mp4 |
40.03Мб |
| 01. Finding the Job - What to Expect and What to Look for.vtt |
4.66Кб |
| 01. For Loops.mp4 |
12.96Мб |
| 01. For Loops.vtt |
6.77Кб |
| 01. For-Loops-Exercise-Py3.ipynb |
1.28Кб |
| 01. For-Loops-Lecture-Py3.ipynb |
1.26Кб |
| 01. For-Loops-Solution-Py3.ipynb |
1.80Кб |
| 01. Fundamentals of Combinatorics.mp4 |
5.94Мб |
| 01. Fundamentals of Combinatorics.vtt |
1.47Кб |
| 01. Fundamentals of Probability Distributions.mp4 |
19.42Мб |
| 01. Fundamentals of Probability Distributions.vtt |
8.40Кб |
| 01. Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 |
19.67Мб |
| 01. Game Plan for this Python, SQL, and Tableau Business Exercise.vtt |
5.57Кб |
| 01. Glossary.xlsx |
19.97Кб |
| 01. How to Install TensorFlow 2.0.mp4 |
27.34Мб |
| 01. How to Install TensorFlow 2.0.vtt |
6.57Кб |
| 01. Introduction.mp4 |
3.06Мб |
| 01. Introduction.vtt |
1.67Кб |
| 01. Introduction to Cluster Analysis.mp4 |
14.46Мб |
| 01. Introduction to Cluster Analysis.vtt |
4.96Кб |
| 01. Introduction to Logistic Regression.mp4 |
5.87Мб |
| 01. Introduction to Logistic Regression.vtt |
1.82Кб |
| 01. Introduction to Neural Networks.mp4 |
10.49Мб |
| 01. Introduction to Neural Networks.vtt |
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| 01. Introduction to pandas Series.mp4 |
24.96Мб |
| 01. Introduction to pandas Series.vtt |
10.85Кб |
| 01. Introduction to Programming.mp4 |
14.87Мб |
| 01. Introduction to Programming.vtt |
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| 01. Introduction-to-Python-Course-Notes.pdf |
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| 01. Introduction-to-Python-Course-Notes.pdf |
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| 01. Introduction to Regression Analysis.mp4 |
3.59Мб |
| 01. Introduction to Regression Analysis.vtt |
2.33Кб |
| 01. Introduction-to-the-If-Statement-Exercise-Py3.ipynb |
1.53Кб |
| 01. Introduction-to-the-If-Statement-Lecture-Py3.ipynb |
1.14Кб |
| 01. Introduction-to-the-If-Statement-Solution-Py3.ipynb |
2.19Кб |
| 01. Intro to the Case Study.mp4 |
10.42Мб |
| 01. Intro to the Case Study.vtt |
3.74Кб |
| 01. K-Means Clustering.mp4 |
10.82Мб |
| 01. K-Means Clustering.vtt |
6.60Кб |
| 01. Lending-company.csv |
112.43Кб |
| 01. Lists.mp4 |
23.04Мб |
| 01. Lists.vtt |
10.35Кб |
| 01. Lists-Exercise-Py3.ipynb |
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| 01. Lists-Lecture-Py3.ipynb |
2.70Кб |
| 01. Lists-Solution-Py3.ipynb |
3.18Кб |
| 01. Location.csv |
13.49Кб |
| 01. Minimal-example-Part-1.ipynb |
1.19Кб |
| 01. MNIST The Dataset.mp4 |
4.53Мб |
| 01. MNIST The Dataset.vtt |
3.65Кб |
| 01. MNIST What is the MNIST Dataset.mp4 |
4.80Мб |
| 01. MNIST What is the MNIST Dataset.vtt |
3.60Кб |
| 01. model |
1.01Кб |
| 01. Multiple Linear Regression.mp4 |
5.68Мб |
| 01. Multiple Linear Regression.vtt |
3.46Кб |
| 01. Necessary Programming Languages and Software Used in Data Science.mp4 |
82.38Мб |
| 01. Necessary Programming Languages and Software Used in Data Science.vtt |
7.97Кб |
| 01. Null vs Alternative Hypothesis.mp4 |
31.94Мб |
| 01. Null vs Alternative Hypothesis.vtt |
7.16Кб |
| 01. Object Oriented Programming.mp4 |
8.66Мб |
| 01. Object Oriented Programming.vtt |
6.86Кб |
| 01. pandas-Fundamentals-Exercises.ipynb |
30.96Кб |
| 01. pandas-Fundamentals-Lectures.ipynb |
21.31Кб |
| 01. pandas-Fundamentals-Solutions.ipynb |
118.35Кб |
| 01. Population and Sample.mp4 |
35.10Мб |
| 01. Population and Sample.vtt |
5.84Кб |
| 01. Practical Example Descriptive Statistics.mp4 |
130.53Мб |
| 01. Practical Example Descriptive Statistics.vtt |
20.99Кб |
| 01. Practical Example Hypothesis Testing.mp4 |
45.83Мб |
| 01. Practical Example Hypothesis Testing.vtt |
8.62Кб |
| 01. Practical Example Inferential Statistics.mp4 |
69.01Мб |
| 01. Practical Example Inferential Statistics.vtt |
13.91Кб |
| 01. Practical Example Linear Regression (Part 1).mp4 |
84.74Мб |
| 01. Practical Example Linear Regression (Part 1).vtt |
14.86Кб |
| 01. Preprocessing Introduction.mp4 |
9.23Мб |
| 01. Preprocessing Introduction.vtt |
4.07Кб |
| 01. Probability in Finance.mp4 |
40.35Мб |
| 01. Probability in Finance.vtt |
10.08Кб |
| 01. Probability-in-Finance-Homework.pdf |
110.68Кб |
| 01. Probability-in-Finance-Solutions.pdf |
184.46Кб |
| 01. READ ME!!!!.html |
564б |
| 01. Region.csv |
10.22Кб |
| 01. Sales-products.csv |
152.28Кб |
| 01. scaler |
1.86Кб |
| 01. Sets and Events.mp4 |
17.67Мб |
| 01. Sets and Events.vtt |
5.45Кб |
| 01. Shortcuts-for-Jupyter.pdf |
619.17Кб |
| 01. Shortcuts-for-Jupyter.pdf |
619.17Кб |
| 01. sklearn-Linear-Regression-Practical-Example-Part-1.ipynb |
166.91Кб |
| 01. sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb |
171.38Кб |
| 01. Statistics-Glossary.xlsx |
20.26Кб |
| 01. Stochastic Gradient Descent.mp4 |
7.83Мб |
| 01. Stochastic Gradient Descent.vtt |
4.83Кб |
| 01. Summary on What You've Learned.mp4 |
9.84Мб |
| 01. Summary on What You've Learned.vtt |
5.48Кб |
| 01. Techniques for Working with Traditional Data.mp4 |
107.18Мб |
| 01. Techniques for Working with Traditional Data.vtt |
10.96Кб |
| 01. The Basic Probability Formula.mp4 |
29.40Мб |
| 01. The Basic Probability Formula.vtt |
8.96Кб |
| 01. The IF Statement.mp4 |
6.71Мб |
| 01. The IF Statement.vtt |
3.73Кб |
| 01. The Linear Regression Model.mp4 |
13.48Мб |
| 01. The Linear Regression Model.vtt |
8.13Кб |
| 01. The Reason Behind These Disciplines.mp4 |
46.77Мб |
| 01. The Reason Behind These Disciplines.vtt |
6.54Кб |
| 01. Traditional data science methods and the role of ChatGPT.mp4 |
26.16Мб |
| 01. Traditional data science methods and the role of ChatGPT.vtt |
7.20Кб |
| 01. Types of Clustering.mp4 |
9.01Мб |
| 01. Types of Clustering.vtt |
5.07Кб |
| 01. Types of Data.mp4 |
43.19Мб |
| 01. Types of Data.vtt |
5.82Кб |
| 01. Using Arithmetic Operators in Python.mp4 |
8.63Мб |
| 01. Using Arithmetic Operators in Python.vtt |
4.37Кб |
| 01. Using the .format() Method.mp4 |
25.69Мб |
| 01. Using the .format() Method.vtt |
12.66Кб |
| 01. Variables.mp4 |
8.94Мб |
| 01. Variables.vtt |
4.80Кб |
| 01. Variables-Exercise-Py3.ipynb |
2.23Кб |
| 01. Variables-Lecture-Py3.ipynb |
3.61Кб |
| 01. Variables-Solution-Py3.ipynb |
3.79Кб |
| 01. What are Confidence Intervals.mp4 |
28.61Мб |
| 01. What are Confidence Intervals.vtt |
3.22Кб |
| 01. What are Data, Servers, Clients, Requests, and Responses.mp4 |
19.51Мб |
| 01. What are Data, Servers, Clients, Requests, and Responses.vtt |
6.29Кб |
| 01. What is a Layer.mp4 |
5.17Мб |
| 01. What is a Layer.vtt |
2.65Кб |
| 01. What is a Matrix.mp4 |
11.94Мб |
| 01. What is a Matrix.vtt |
4.63Кб |
| 01. What is Initialization.mp4 |
8.90Мб |
| 01. What is Initialization.vtt |
3.74Кб |
| 01. What is Overfitting.mp4 |
10.81Мб |
| 01. What is Overfitting.vtt |
5.87Кб |
| 01. What is sklearn and How is it Different from Other Packages.mp4 |
8.48Мб |
| 01. What is sklearn and How is it Different from Other Packages.vtt |
3.62Кб |
| 01. What to Expect from the Following Sections.html |
2.48Кб |
| 01. What to Expect from this Part.mp4 |
11.72Мб |
| 01. What to Expect from this Part.vtt |
4.83Кб |
| 02. 1.02.Multiple-linear-regression.csv |
1.09Кб |
| 02. 1.04.Real-life-example.csv |
219.83Кб |
| 02. 2.01.Admittance.csv |
1.58Кб |
| 02. 2.13.Practical-example.Descriptive-statistics-exercise.xlsx |
120.27Кб |
| 02. 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx |
146.38Кб |
| 02. 3.01.Country-clusters.csv |
200б |
| 02. 3.17.Practical-example.Confidence-intervals-exercise.xlsx |
1.73Мб |
| 02. 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx |
1.82Мб |
| 02. 3.2.What-is-a-distribution-lesson.xlsx |
19.46Кб |
| 02. 3.9.Population-variance-known-z-score-lesson.xlsx |
11.21Кб |
| 02. 3.9.The-z-table.xlsx |
25.58Кб |
| 02. 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx |
43.69Кб |
| 02. 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx |
44.27Кб |
| 02. Absenteeism-predictions.csv |
2.10Кб |
| 02. Add-an-Else-Statement-Exercise-Py3.ipynb |
1.02Кб |
| 02. Add-an-Else-Statement-Lecture-Py3.ipynb |
1.76Кб |
| 02. Add-an-Else-Statement-Solution-Py3.ipynb |
1.40Кб |
| 02. Adjusted R-Squared.mp4 |
34.20Мб |
| 02. Adjusted R-Squared.vtt |
7.51Кб |
| 02. Admittance.ipynb |
3.54Кб |
| 02. Admittance-with-comments.ipynb |
5.32Кб |
| 02. Analyzing Age vs Probability in Tableau.mp4 |
38.68Мб |
| 02. Analyzing Age vs Probability in Tableau.vtt |
10.24Кб |
| 02. A Note on Completing the Upcoming Coding Exercises.html |
2.96Кб |
| 02. A Simple Example in Python.mp4 |
21.88Мб |
| 02. A Simple Example in Python.vtt |
5.91Кб |
| 02. A Simple Example of Clustering.mp4 |
34.18Мб |
| 02. A Simple Example of Clustering.vtt |
9.74Кб |
| 02. Basic NN Example (Part 2).mp4 |
15.23Мб |
| 02. Basic NN Example (Part 2).vtt |
6.69Кб |
| 02. Business Case Outlining the Solution.mp4 |
3.04Мб |
| 02. Business Case Outlining the Solution.mp4 |
4.16Мб |
| 02. Business Case Outlining the Solution.vtt |
1.91Кб |
| 02. Business Case Outlining the Solution.vtt |
2.60Кб |
| 02. Computing Expected Values.mp4 |
45.66Мб |
| 02. Computing Expected Values.vtt |
6.95Кб |
| 02. Confidence Intervals; Population Variance Known; Z-score.mp4 |
52.16Мб |
| 02. Confidence Intervals; Population Variance Known; Z-score.vtt |
9.61Кб |
| 02. Correlation vs Regression.mp4 |
3.84Мб |
| 02. Correlation vs Regression.vtt |
2.16Кб |
| 02. Country-clusters.ipynb |
3.31Кб |
| 02. Country-clusters-with-comments.ipynb |
5.80Кб |
| 02. Course-Notes-Cluster-Analysis.pdf |
208.65Кб |
| 02. Course-notes-inferential-statistics.pdf |
382.32Кб |
| 02. Course-Notes-Logistic-Regression.pdf |
335.17Кб |
| 02. Course-Notes-Section-2.pdf |
578.08Кб |
| 02. Course-Notes-Section-6.pdf |
936.42Кб |
| 02. Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb |
1.16Кб |
| 02. Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb |
1.59Кб |
| 02. Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb |
1.79Кб |
| 02. Creating the Targets for the Logistic Regression.mp4 |
32.44Мб |
| 02. Creating the Targets for the Logistic Regression.vtt |
8.72Кб |
| 02. Dendrogram.mp4 |
18.29Мб |
| 02. Dendrogram.vtt |
7.58Кб |
| 02. Deploying the 'absenteeism_module' - Part I.mp4 |
19.67Мб |
| 02. Deploying the 'absenteeism_module' - Part I.vtt |
4.98Кб |
| 02. Further Reading on Null and Alternative Hypothesis.html |
2.29Кб |
| 02. Help-Yourself-with-Methods-Exercise-Py3.ipynb |
1.91Кб |
| 02. Help-Yourself-with-Methods-Lecture-Py3.ipynb |
4.39Кб |
| 02. Help-Yourself-with-Methods-Solution-Py3.ipynb |
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| 02. How are we Going to Approach this Section.mp4 |
5.30Мб |
| 02. How are we Going to Approach this Section.vtt |
3.03Кб |
| 02. How to Create a Function with a Parameter.mp4 |
9.99Мб |
| 02. How to Create a Function with a Parameter.vtt |
4.52Кб |
| 02. How to install ChatGPT.mp4 |
5.22Мб |
| 02. How to install ChatGPT.vtt |
2.05Кб |
| 02. How to Install TensorFlow 1.mp4 |
5.00Мб |
| 02. How to Install TensorFlow 1.vtt |
3.40Кб |
| 02. Importing the Absenteeism Data in Python.mp4 |
19.52Мб |
| 02. Importing the Absenteeism Data in Python.vtt |
4.04Кб |
| 02. Iterating Over Range Objects.mp4 |
12.61Мб |
| 02. Iterating Over Range Objects.vtt |
6.43Кб |
| 02. Levels of Measurement.mp4 |
32.19Мб |
| 02. Levels of Measurement.vtt |
4.83Кб |
| 02. Logical and Identity Operators.mp4 |
19.01Мб |
| 02. Logical and Identity Operators.vtt |
5.97Кб |
| 02. Logical-and-Identity-Operators-Lecture-Py3.ipynb |
5.86Кб |
| 02. Logical-and-Identity-Operators-Solution-Py3.ipynb |
3.43Кб |
| 02. Minimal-example-Part-2.ipynb |
3.65Кб |
| 02. MNIST How to Tackle the MNIST.mp4 |
7.94Мб |
| 02. MNIST How to Tackle the MNIST.mp4 |
8.01Мб |
| 02. MNIST How to Tackle the MNIST.vtt |
3.63Кб |
| 02. MNIST How to Tackle the MNIST.vtt |
3.84Кб |
| 02. Modules and Packages.mp4 |
2.08Мб |
| 02. Modules and Packages.vtt |
1.45Кб |
| 02. Multiple-linear-regression-and-Adjusted-R-squared.ipynb |
2.15Кб |
| 02. Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb |
2.80Кб |
| 02. Numbers-and-Boolean-Values-Exercise-Py3.ipynb |
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| 02. Numbers and Boolean Values in Python.mp4 |
6.57Мб |
| 02. Numbers and Boolean Values in Python.vtt |
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| 02. Numbers-and-Boolean-Values-Lecture-Py3.ipynb |
3.36Кб |
| 02. Numbers-and-Boolean-Values-Solution-Py3.ipynb |
3.23Кб |
| 02. Permutations and How to Use Them.mp4 |
17.52Мб |
| 02. Permutations and How to Use Them.vtt |
4.41Кб |
| 02. Practical Example Descriptive Statistics Exercise.html |
81б |
| 02. Practical Example Hypothesis Testing Exercise.html |
81б |
| 02. Practical Example Inferential Statistics Exercise.html |
81б |
| 02. Practical Example Linear Regression (Part 2).mp4 |
31.86Мб |
| 02. Practical Example Linear Regression (Part 2).vtt |
8.33Кб |
| 02. Probability in Statistics.mp4 |
31.60Мб |
| 02. Probability in Statistics.vtt |
9.12Кб |
| 02. Problems with Gradient Descent.mp4 |
3.65Мб |
| 02. Problems with Gradient Descent.vtt |
2.99Кб |
| 02. Real Life Examples of Traditional Data.mp4 |
18.37Мб |
| 02. Real Life Examples of Traditional Data.vtt |
2.33Кб |
| 02. Scalars and Vectors.mp4 |
8.54Мб |
| 02. Scalars and Vectors.vtt |
4.01Кб |
| 02. sklearn-Linear-Regression-Practical-Example-Part-2.ipynb |
328.74Кб |
| 02. sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb |
335.63Кб |
| 02. Some Examples of Clusters.mp4 |
35.86Мб |
| 02. Some Examples of Clusters.vtt |
6.25Кб |
| 02. TensorFlow Outline and Comparison with Other Libraries.mp4 |
15.29Мб |
| 02. TensorFlow Outline and Comparison with Other Libraries.vtt |
5.49Кб |
| 02. The Business Task.mp4 |
11.28Мб |
| 02. The Business Task.vtt |
4.07Кб |
| 02. The Double Equality Sign.mp4 |
2.72Мб |
| 02. The Double Equality Sign.vtt |
1.90Кб |
| 02. The-Double-Equality-Sign-Exercise-Py3.ipynb |
838б |
| 02. The-Double-Equality-Sign-Lecture-Py3.ipynb |
1.45Кб |
| 02. The-Double-Equality-Sign-Solution-Py3.ipynb |
1.14Кб |
| 02. The ELSE Statement.mp4 |
6.04Мб |
| 02. The ELSE Statement.vtt |
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| 02. The Naive Bayes Algorithm.mp4 |
42.06Мб |
| 02. The Naive Bayes Algorithm.vtt |
6.08Кб |
| 02. Training the Model.mp4 |
7.72Мб |
| 02. Training the Model.vtt |
4.74Кб |
| 02. Types of Basic Preprocessing.mp4 |
3.25Мб |
| 02. Types of Basic Preprocessing.vtt |
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| 02. Types of Probability Distributions.mp4 |
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| 32. Final Remarks of this Section.mp4 |
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| 33. A Note on Exporting Your Data as a .csv File.html |
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