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文档列表

6. Gradient Descent/4. Creating Normal Histogram.mp4 68.1 MB
4. Linear Algebra/4. Understanding Central Tendencies.mp4 66.0 MB
5. Probability/7. Defining the Next Value.mp4 62.5 MB
6. Gradient Descent/1. Value Import.mp4 61.7 MB
6. Gradient Descent/3. Working with Data Analysis.mp4 58.9 MB
4. Linear Algebra/2. Matrices in Linear Algebra.mp4 55.6 MB
6. Gradient Descent/2. Output Functions for Gradient.mp4 54.2 MB
5. Probability/6. Example on Hypothesis Testing.mp4 51.7 MB
6. Gradient Descent/5. Two Dimensional Graph.mp4 51.5 MB
6. Gradient Descent/6. Multiple Scatter Plots.mp4 47.7 MB
5. Probability/2. Normal Distribution Curve.mp4 45.8 MB
6. Gradient Descent/8. Learnig Box Plots.mp4 41.8 MB
3. Advanced Python/4. Creating Bar Charts.mp4 40.8 MB
5. Probability/2. Normal Distribution Curve.vtt 39.9 MB
5. Probability/4. Central Limit Theorem.mp4 38.6 MB
4. Linear Algebra/1. Vector Spaces in Linear Algebra.mp4 37.2 MB
3. Advanced Python/6. Understanding Scattered Plots.mp4 36.8 MB
6. Gradient Descent/7. Analyzing Data Sets.mp4 36.3 MB
4. Linear Algebra/5. Dispersion for Data.mp4 36.0 MB
5. Probability/3. Example for Normal Distribution Curve.mp4 34.1 MB
5. Probability/12. Example on Gradient Descent.mp4 33.2 MB
5. Probability/10. Line of Best Fit.mp4 32.1 MB
3. Advanced Python/5. Analysis on Line Chart.mp4 31.8 MB
4. Linear Algebra/3. Analysing Statistical Data.mp4 30.5 MB
2. What is Data Science/3. Various Python Scripts.mp4 30.1 MB
5. Probability/9. Understanding Bayesian Inference.mp4 29.2 MB
2. What is Data Science/2. Python Environment Framework.mp4 28.9 MB
5. Probability/8. Principle of P Hacking.mp4 28.7 MB
3. Advanced Python/1. Concept of Advanced Python.mp4 27.8 MB
5. Probability/5. Concept of Hypothesis.mp4 27.5 MB
3. Advanced Python/2. Creating Functions for Python.mp4 24.7 MB
3. Advanced Python/3. Creating a New Library.mp4 23.9 MB
5. Probability/1. Probability in Discreet Mathematics.mp4 21.6 MB
2. What is Data Science/1. Understanding Data Science.mp4 18.9 MB
1. Introduction/1. Introduction to Data Visualization.mp4 17.8 MB
5. Probability/11. Datascience with Gradient Descent.mp4 14.5 MB
7. Conclusion/1. Overview and Conclusion.mp4 13.6 MB
1. Introduction/1.1 Data Science with Python.zip.zip 910.3 kB
4. Linear Algebra/2. Matrices in Linear Algebra.vtt 10.2 kB
4. Linear Algebra/4. Understanding Central Tendencies.vtt 10.0 kB
6. Gradient Descent/3. Working with Data Analysis.vtt 8.6 kB
3. Advanced Python/4. Creating Bar Charts.vtt 7.8 kB
5. Probability/7. Defining the Next Value.vtt 7.8 kB
5. Probability/6. Example on Hypothesis Testing.vtt 6.6 kB
2. What is Data Science/3. Various Python Scripts.vtt 6.6 kB
6. Gradient Descent/4. Creating Normal Histogram.vtt 6.6 kB
4. Linear Algebra/1. Vector Spaces in Linear Algebra.vtt 6.5 kB
3. Advanced Python/1. Concept of Advanced Python.vtt 6.4 kB
5. Probability/4. Central Limit Theorem.vtt 6.3 kB
6. Gradient Descent/1. Value Import.vtt 6.2 kB
4. Linear Algebra/3. Analysing Statistical Data.vtt 6.2 kB
6. Gradient Descent/6. Multiple Scatter Plots.vtt 6.1 kB
2. What is Data Science/1. Understanding Data Science.vtt 5.9 kB
3. Advanced Python/6. Understanding Scattered Plots.vtt 5.9 kB
6. Gradient Descent/8. Learnig Box Plots.vtt 5.8 kB
6. Gradient Descent/5. Two Dimensional Graph.vtt 5.7 kB
3. Advanced Python/5. Analysis on Line Chart.vtt 5.7 kB
6. Gradient Descent/2. Output Functions for Gradient.vtt 5.6 kB
6. Gradient Descent/7. Analyzing Data Sets.vtt 5.6 kB
4. Linear Algebra/5. Dispersion for Data.vtt 5.4 kB
5. Probability/3. Example for Normal Distribution Curve.vtt 5.3 kB
5. Probability/9. Understanding Bayesian Inference.vtt 5.2 kB
2. What is Data Science/2. Python Environment Framework.vtt 5.0 kB
5. Probability/12. Example on Gradient Descent.vtt 5.0 kB
1. Introduction/1. Introduction to Data Visualization.vtt 4.9 kB
3. Advanced Python/3. Creating a New Library.vtt 4.8 kB
3. Advanced Python/2. Creating Functions for Python.vtt 4.5 kB
5. Probability/8. Principle of P Hacking.vtt 4.4 kB
5. Probability/10. Line of Best Fit.vtt 4.4 kB
5. Probability/1. Probability in Discreet Mathematics.vtt 4.4 kB
5. Probability/5. Concept of Hypothesis.vtt 4.2 kB
7. Conclusion/1. Overview and Conclusion.vtt 4.1 kB
5. Probability/11. Datascience with Gradient Descent.vtt 3.8 kB
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