21. Statistics - Practical Example Hypothesis Testing/1. Practical Example Hypothesis Testing.mp4 72.9 MB
56. Software Integration/1. What are Data, Servers, Clients, Requests, and Responses.mp4 72.4 MB
12. Probability - Distributions/11. Discrete Distributions The Binomial Distribution.mp4 72.2 MB
2. The Field of Data Science - The Various Data Science Disciplines/9. A Breakdown of our Data Science Infographic.mp4 71.0 MB
51. Deep Learning - Business Case Example/1. Business Case Exploring the Dataset and Identifying Predictors.mp4 69.5 MB
2. The Field of Data Science - The Various Data Science Disciplines/5. Business Analytics, Data Analytics, and Data Science An Introduction.mp4 67.6 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/6. Fitting the Model and Assessing its Accuracy.mp4 43.6 MB
50. Deep Learning - Classifying on the MNIST Dataset/6. MNIST Preprocess the Data - Shuffle and Batch.mp4 43.5 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/8. Business Case Optimization.mp4 43.5 MB
10. Probability - Combinatorics/17. Combinatorics in Real-Life The Lottery.mp4 43.3 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/9. Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4 43.2 MB
32. Advanced Statistical Methods - Linear regression with StatsModels/17. R-Squared.mp4 43.0 MB
50. Deep Learning - Classifying on the MNIST Dataset/10. MNIST Learning.mp4 43.0 MB
57. Case Study - What's Next in the Course/3. Introducing the Data Set.mp4 42.9 MB
61. Case Study - Analyzing the Predicted Outputs in Tableau/6. Analyzing Transportation Expense vs Probability in Tableau.mp4 42.6 MB
32. Advanced Statistical Methods - Linear regression with StatsModels/7. Python Packages Installation.mp4 42.6 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/10. Analyzing the Reasons for Absence.mp4 42.5 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/10. Interpreting the Coefficients of the Logistic Regression.mp4 42.4 MB
10. Probability - Combinatorics/13. Symmetry of Combinations.mp4 42.3 MB
20. Statistics - Hypothesis Testing/12. Test for the Mean. Population Variance Unknown.mp4 42.2 MB
12. Probability - Distributions/25. Continuous Distributions The Exponential Distribution.mp4 42.2 MB
52. Deep Learning - Conclusion/1. Summary on What You've Learned.mp4 41.7 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/31. Working on Education, Children, and Pets.mp4 41.5 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/11. Backward Elimination or How to Simplify Your Model.mp4 41.5 MB
42. Deep Learning - Introduction to Neural Networks/23. Optimization Algorithm n-Parameter Gradient Descent.mp4 41.3 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/3. The Importance of Working with a Balanced Dataset.mp4 41.3 MB
57. Case Study - What's Next in the Course/2. The Business Task.mp4 41.1 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/14. Feature Scaling (Standardization).mp4 41.0 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/7. Creating a Summary Table with the Coefficients and Intercept.mp4 40.8 MB
44. Deep Learning - TensorFlow 2.0 Introduction/1. How to Install TensorFlow 2.0.mp4 40.6 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/17. Using .concat() in Python.mp4 40.6 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/7. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4 40.4 MB
10. Probability - Combinatorics/19. A Recap of Combinatorics.mp4 40.4 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/4. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4 33.6 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/4. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4 30.5 MB
39. Advanced Statistical Methods - Other Types of Clustering/2. Dendrogram.mp4 30.5 MB
50. Deep Learning - Classifying on the MNIST Dataset/4. MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4 30.5 MB
49. Deep Learning - Preprocessing/5. Binary and One-Hot Encoding.mp4 30.4 MB
12. Probability - Distributions/15.1 Solving Integrals.pdf.pdf 352.1 kB
2. The Field of Data Science - The Various Data Science Disciplines/5.1 365_DataScience_Diagram.pdf.pdf 330.8 kB
2. The Field of Data Science - The Various Data Science Disciplines/7.1 365_DataScience_Diagram.pdf.pdf 330.8 kB
1. Part 1 Introduction/3.1 FAQ_The_Data_Science_Course.pdf.pdf 313.4 kB
15. Statistics - Descriptive Statistics/13.2 Statistics - PDF with Excel Solutions that don't visualize properly.pdf.pdf 296.1 kB
15. Statistics - Descriptive Statistics/7.2 Statistics - PDF with Excel Solutions that don't visualize properly.pdf.pdf 296.1 kB
10. Probability - Combinatorics/20.2 Additional Exercises Combinatorics Solutions.pdf.pdf 251.6 kB
10. Probability - Combinatorics/1.1 Course Notes - Combinatorics.pdf.pdf 231.5 kB
10. Probability - Combinatorics/11.1 Combinations With Repetition.pdf.pdf 212.4 kB
13. Probability - Probability in Other Fields/1.1 Probability in Finance Solutions.pdf.pdf 188.9 kB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/9.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf.pdf 186.7 kB
51. Deep Learning - Business Case Example/1. Business Case Exploring the Dataset and Identifying Predictors.srt 10.9 kB
2. The Field of Data Science - The Various Data Science Disciplines/5. Business Analytics, Data Analytics, and Data Science An Introduction.srt 10.9 kB
5. The Field of Data Science - Popular Data Science Techniques/1. Techniques for Working with Traditional Data.srt 10.9 kB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/3. Digging into a Deep Net.srt 6.9 kB
34. Advanced Statistical Methods - Linear Regression with sklearn/4. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.srt 6.9 kB
13. Probability - Probability in Other Fields/3. Probability in Data Science.srt 6.8 kB
2. The Field of Data Science - The Various Data Science Disciplines/1. Data Science and Business Buzzwords Why are there so many.srt 6.8 kB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/7. Creating a Summary Table with the Coefficients and Intercept.srt 6.8 kB
15. Statistics - Descriptive Statistics/24. Standard Deviation and Coefficient of Variation.srt 6.8 kB
55. Appendix Deep Learning - TensorFlow 1 Business Case/8. Business Case Optimization.srt 6.8 kB
29. Python - Iterations/1. For Loops.srt 6.7 kB
32. Advanced Statistical Methods - Linear regression with StatsModels/17. R-Squared.srt 6.7 kB
12. Probability - Distributions/13. Discrete Distributions The Poisson Distribution.srt 6.7 kB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/6. Calculating the Accuracy of the Model.srt 5.3 kB
20. Statistics - Hypothesis Testing/18. Test for the mean. Independent samples (Part 2).srt 5.3 kB
52. Deep Learning - Conclusion/6. An Overview of non-NN Approaches.srt 5.2 kB
2. The Field of Data Science - The Various Data Science Disciplines/9. A Breakdown of our Data Science Infographic.srt 5.2 kB
1. Part 1 Introduction/2. What Does the Course Cover.srt 5.2 kB
58. Case Study - Preprocessing the 'Absenteeism_data'/17. Using .concat() in Python.srt 5.2 kB
2. The Field of Data Science - The Various Data Science Disciplines/3. What is the difference between Analysis and Analytics.srt 5.2 kB
11. Probability - Bayesian Inference/1. Sets and Events.srt 5.2 kB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/9. Standardizing only the Numerical Variables (Creating a Custom Scaler).srt 5.1 kB
12. Probability - Distributions/27. Continuous Distributions The Logistic Distribution.srt 5.1 kB
61. Case Study - Analyzing the Predicted Outputs in Tableau/5. EXERCISE - Transportation Expense vs Probability.html 553 Bytes
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/9. Backpropagation - A Peek into the Mathematics of Optimization.html 539 Bytes
2. The Field of Data Science - The Various Data Science Disciplines/10. A Breakdown of our Data Science Infographic.html 165 Bytes
2. The Field of Data Science - The Various Data Science Disciplines/2. Data Science and Business Buzzwords Why are there so many.html 165 Bytes
2. The Field of Data Science - The Various Data Science Disciplines/4. What is the difference between Analysis and Analytics.html 165 Bytes
2. The Field of Data Science - The Various Data Science Disciplines/6. Business Analytics, Data Analytics, and Data Science An Introduction.html 165 Bytes
2. The Field of Data Science - The Various Data Science Disciplines/8. Continuing with BI, ML, and AI.html 165 Bytes