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文件列表

  • 25. Neural Nets and Deep Learning/30. Tensorboard.mp4 151.2 MB
  • 25. Neural Nets and Deep Learning/23. Keras Project Solutions - Dealing with Missing Data.mp4 150.6 MB
  • 25. Neural Nets and Deep Learning/15. TF Regression Code Along - Exploratory Data Analysis.mp4 143.6 MB
  • 25. Neural Nets and Deep Learning/26. Keras Project Solutions - Data PreProcessing.mp4 131.0 MB
  • 25. Neural Nets and Deep Learning/20. TF Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
  • 25. Neural Nets and Deep Learning/24. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 101.5 MB
  • 25. Neural Nets and Deep Learning/25. Keras Project Solutions - Categorical Data.mp4 89.5 MB
  • 25. Neural Nets and Deep Learning/13. TF Syntax Basics - Part Two - Creating and Training the Model.mp4 88.4 MB
  • 14. Introduction to Machine Learning/4. Evaluating Performance - Classification Error Metrics.mp4 86.7 MB
  • 25. Neural Nets and Deep Learning/22. TensorFlow 2.0 Project Notebook Overview.mp4 84.4 MB
  • 2. Environment Set-Up/1. Python Environment Setup.mp4 80.1 MB
  • 25. Neural Nets and Deep Learning/16. TF Regression Code Along - Exploratory Data Analysis - Continued.mp4 79.9 MB
  • 25. Neural Nets and Deep Learning/9. Cost Functions and Gradient Descent.mp4 79.7 MB
  • 25. Neural Nets and Deep Learning/18. TF Regression Code Along - Model Evaluation and Predictions.mp4 72.3 MB
  • 25. Neural Nets and Deep Learning/14. TF Syntax Basics - Part Three - Model Evaluation.mp4 67.9 MB
  • 25. Neural Nets and Deep Learning/29. Keras Project Solutions - Model Evaluation.mp4 66.2 MB
  • 26. Big Data and Spark with Python/7. EC2 Instance Set-Up.mp4 66.0 MB
  • 25. Neural Nets and Deep Learning/7. Activation Functions.mp4 65.6 MB
  • 26. Big Data and Spark with Python/9. PySpark Setup.mp4 63.3 MB
  • 25. Neural Nets and Deep Learning/10. Backpropagation.mp4 60.8 MB
  • 25. Neural Nets and Deep Learning/19. TF Classification Code Along - EDA and Preprocessing.mp4 58.9 MB
  • 26. Big Data and Spark with Python/12. RDD Transformations and Actions.mp4 58.4 MB
  • 18. K Nearest Neighbors/4. KNN Project Solutions.mp4 55.2 MB
  • 1. Course Introduction/3.1 Py_DS_ML_Bootcamp-master.zip.zip 55.1 MB
  • 3. Jupyter Overview/2.1 Py-DS-ML-Bootcamp-master.zip.zip 55.1 MB
  • 2. Environment Set-Up/1.1 Py-DS-ML-Bootcamp-master.zip.zip 55.0 MB
  • 9. Python for Data Visualization - Seaborn/2. Distribution Plots.srt 53.9 MB
  • 9. Python for Data Visualization - Seaborn/2. Distribution Plots.mp4 53.9 MB
  • 11. Python for Data Visualization - Plotly and Cufflinks/2. Plotly and Cufflinks.mp4 53.6 MB
  • 25. Neural Nets and Deep Learning/12. TF Syntax Basics - Part One - Preparing the Data.mp4 52.8 MB
  • 13. Data Capstone Project/4. 911 Calls Solutions - Part 2.mp4 52.2 MB
  • 24. Natural Language Processing/6. NLP Project Solutions.mp4 50.4 MB
  • 25. Neural Nets and Deep Learning/5. Perceptron Model.mp4 50.3 MB
  • 20. Support Vector Machines/2. Support Vector Machines with Python.mp4 49.8 MB
  • 13. Data Capstone Project/7. Finance Project - Solutions Part 1.mp4 49.6 MB
  • 21. K Means Clustering/4. K Means Project Solutions.mp4 49.4 MB
  • 25. Neural Nets and Deep Learning/17. TF Regression Code Along - Data Preprocessing and Creating a Model.mp4 49.3 MB
  • 12. Python for Data Visualization - Geographical Plotting/2. Choropleth Maps - Part 1 - USA.mp4 48.4 MB
  • 25. Neural Nets and Deep Learning/8. Multi-Class Classification Considerations.mp4 48.3 MB
  • 18. K Nearest Neighbors/2. KNN with Python.mp4 48.2 MB
  • 13. Data Capstone Project/8. Finance Project - Solutions Part 2.mp4 47.9 MB
  • 15. Linear Regression/6. Linear Regression Project Solution.mp4 47.6 MB
  • 15. Linear Regression/3. Linear Regression with Python - Part 1.mp4 45.4 MB
  • 22. Principal Component Analysis/2. PCA with Python.mp4 45.3 MB
  • 7. Python for Data Analysis - Pandas Exercises/5. Ecommerce Purchases Exercise Solutions.mp4 45.2 MB
  • 7. Python for Data Analysis - Pandas Exercises/3. SF Salaries Solutions.mp4 44.8 MB
  • 6. Python for Data Analysis - Pandas/5. DataFrames - Part 2.mp4 44.1 MB
  • 24. Natural Language Processing/3. NLP with Python - Part 2.mp4 44.0 MB
  • 17. Logistic Regression/2. Logistic Regression with Python - Part 1.mp4 43.4 MB
  • 24. Natural Language Processing/2. NLP with Python - Part 1.mp4 42.1 MB
  • 19. Decision Trees and Random Forests/2. Decision Trees and Random Forest with Python.mp4 42.1 MB
  • 14. Introduction to Machine Learning/3. Supervised Learning Overview.mp4 42.0 MB
  • 13. Data Capstone Project/3. 911 Calls Solutions - Part 1.mp4 41.7 MB
  • 6. Python for Data Analysis - Pandas/4. DataFrames - Part 1.mp4 41.7 MB
  • 9. Python for Data Visualization - Seaborn/3. Categorical Plots.mp4 40.4 MB
  • 5. Python for Data Analysis - NumPy/8. Numpy Exercises Solutions.mp4 40.1 MB
  • 24. Natural Language Processing/4. NLP with Python - Part 3.mp4 39.5 MB
  • 13. Data Capstone Project/4. 911 Calls Solutions - Part 2.srt 39.4 MB
  • 5. Python for Data Analysis - NumPy/5. Numpy Array Indexing.mp4 39.1 MB
  • 6. Python for Data Analysis - Pandas/11. Data Input and Output.mp4 38.4 MB
  • 8. Python for Data Visualization - Matplotlib/3. Matplotlib Part 1.mp4 37.9 MB
  • 25. Neural Nets and Deep Learning/6. Neural Networks.mp4 37.7 MB
  • 4. Python Crash Course/3. Python Crash Course - Part 1.mp4 37.5 MB
  • 23. Recommender Systems/2. Recommender Systems with Python - Part 1.mp4 37.3 MB
  • 23. Recommender Systems/3. Recommender Systems with Python - Part 2.mp4 36.1 MB
  • 17. Logistic Regression/3. Logistic Regression with Python - Part 2.mp4 35.9 MB
  • 5. Python for Data Analysis - NumPy/3. Numpy Arrays.mp4 35.1 MB
  • 25. Neural Nets and Deep Learning/1.1 TensorFlow_FILES.zip.zip 34.7 MB
  • 3. Jupyter Overview/2. Jupyter Notebooks.mp4 33.5 MB
  • 4. Python Crash Course/5. Python Crash Course - Part 3.mp4 33.3 MB
  • 8. Python for Data Visualization - Matplotlib/4. Matplotlib Part 2.mp4 33.1 MB
  • 10. Python for Data Visualization - Pandas Built-in Data Visualization/1. Pandas Built-in Data Visualization.mp4 32.9 MB
  • 19. Decision Trees and Random Forests/4. Decision Trees and Random Forest Solutions Part 1.mp4 32.4 MB
  • 17. Logistic Regression/6. Logistic Regression Project Solutions.mp4 31.7 MB
  • 21. K Means Clustering/2. K Means with Python.mp4 31.4 MB
  • 25. Neural Nets and Deep Learning/28. Keras Project Solutions - Creating and Training a Model.mp4 31.2 MB
  • 4. Python Crash Course/6. Python Crash Course - Part 4.mp4 30.7 MB
  • 1. Course Introduction/1. Introduction to the Course.mp4 30.4 MB
  • 4. Python Crash Course/4. Python Crash Course - Part 2.mp4 30.3 MB
  • 10. Python for Data Visualization - Pandas Built-in Data Visualization/3. Pandas Data Visualization Exercise- Solutions.mp4 30.0 MB
  • 20. Support Vector Machines/4. SVM Project Solutions.mp4 29.5 MB
  • 8. Python for Data Visualization - Matplotlib/7. Matplotlib Exercises - Solutions.mp4 29.1 MB
  • 12. Python for Data Visualization - Geographical Plotting/5. Choropleth Exercises - Solutions.mp4 29.0 MB
  • 8. Python for Data Visualization - Matplotlib/5. Matplotlib Part 3.mp4 28.6 MB
  • 4. Python Crash Course/8. Python Crash Course Exercises - Solutions.mp4 28.6 MB
  • 19. Decision Trees and Random Forests/5. Decision Trees and Random Forest Solutions Part 2.mp4 27.8 MB
  • 6. Python for Data Analysis - Pandas/9. Merging Joining and Concatenating.mp4 27.4 MB
  • 5. Python for Data Analysis - NumPy/6. Numpy Operations.mp4 26.7 MB
  • 6. Python for Data Analysis - Pandas/10. Operations.mp4 25.3 MB
  • 25. Neural Nets and Deep Learning/27. Keras Project Solutions - Data PreProcessing.mp4 25.1 MB
  • 14. Introduction to Machine Learning/5. Evaluating Performance - Regression Error Metrics.mp4 24.8 MB
  • 5. Python for Data Analysis - NumPy/3. Numpy Arrays.srt 24.0 MB
  • 9. Python for Data Visualization - Seaborn/4. Matrix Plots.mp4 23.5 MB
  • 17. Logistic Regression/1. Logistic Regression Theory.mp4 22.0 MB
  • 6. Python for Data Analysis - Pandas/6. DataFrames - Part 3.mp4 21.9 MB
  • 6. Python for Data Analysis - Pandas/3. Series.mp4 21.3 MB
  • 9. Python for Data Visualization - Seaborn/9. Seaborn Exercise Solutions.mp4 21.0 MB
  • 9. Python for Data Visualization - Seaborn/5. Grids.mp4 20.8 MB
  • 6. Python for Data Analysis - Pandas/3. Series.srt 20.3 MB
  • 12. Python for Data Visualization - Geographical Plotting/3. Choropleth Maps - Part 2 - World.mp4 20.1 MB
  • 9. Python for Data Visualization - Seaborn/7. Style and Color.mp4 19.9 MB
  • 3. Jupyter Overview/3. Optional Virtual Environments.mp4 19.9 MB
  • 16. Cross Validation and Bias-Variance Trade-Off/1. Bias Variance Trade-Off.mp4 19.8 MB
  • 17. Logistic Regression/4. Logistic Regression with Python - Part 3.mp4 17.8 MB
  • 14. Introduction to Machine Learning/6. Machine Learning with Python.mp4 17.6 MB
  • 13. Data Capstone Project/9. Finance Project - Solutions Part 3.mp4 17.4 MB
  • 15. Linear Regression/4. Linear Regression with Python - Part 2.mp4 16.8 MB
  • 26. Big Data and Spark with Python/11. Introduction to Spark and Python.mp4 16.5 MB
  • 26. Big Data and Spark with Python/3. Spark Overview.mp4 16.5 MB
  • 9. Python for Data Visualization - Seaborn/6. Regression Plots.mp4 16.2 MB
  • 6. Python for Data Analysis - Pandas/8. Groupby.mp4 15.5 MB
  • 8. Python for Data Visualization - Matplotlib/2. Introduction to Matplotlib.mp4 13.3 MB
  • 11. Python for Data Visualization - Plotly and Cufflinks/1. Introduction to Plotly and Cufflinks.mp4 13.1 MB
  • 13. Data Capstone Project/6. Finance Data Project Overview.mp4 12.8 MB
  • 6. Python for Data Analysis - Pandas/7. Missing Data.mp4 12.7 MB
  • 19. Decision Trees and Random Forests/1. Introduction to Tree Methods.mp4 12.6 MB
  • 19. Decision Trees and Random Forests/3. Decision Trees and Random Forest Project Overview.mp4 12.5 MB
  • 12. Python for Data Visualization - Geographical Plotting/4. Choropleth Exercises.mp4 11.7 MB
  • 26. Big Data and Spark with Python/5. AWS Account Set-Up.mp4 11.4 MB
  • 15. Linear Regression/5. Linear Regression Project Overview.mp4 11.3 MB
  • 25. Neural Nets and Deep Learning/11. TensorFlow vs Keras.mp4 11.0 MB
  • 26. Big Data and Spark with Python/2. Big Data Overview.mp4 10.4 MB
  • 18. K Nearest Neighbors/1. KNN Theory.mp4 10.4 MB
  • 5. Python for Data Analysis - NumPy/7. Numpy Exercises Overview.mp4 10.2 MB
  • 25. Neural Nets and Deep Learning/3. Introduction to Artificial Neural Networks (ANN).mp4 10.1 MB
  • 21. K Means Clustering/1. K Means Algorithm Theory.mp4 10.1 MB
  • 4. Python Crash Course/7. Python Crash Course Exercises - Overview.mp4 9.8 MB
  • 26. Big Data and Spark with Python/10. Lambda Expressions Review.mp4 9.8 MB
  • 21. K Means Clustering/3. K Means Project Overview.mp4 9.6 MB
  • 26. Big Data and Spark with Python/8. SSH with Mac or Linux.mp4 9.6 MB
  • 9. Python for Data Visualization - Seaborn/1. Introduction to Seaborn.mp4 9.5 MB
  • 24. Natural Language Processing/1. Natural Language Processing Theory.mp4 9.3 MB
  • 20. Support Vector Machines/1. SVM Theory.mp4 9.1 MB
  • 20. Support Vector Machines/3. SVM Project Overview.mp4 9.0 MB
  • 13. Data Capstone Project/2. 911 Calls Project Overview.mp4 9.0 MB
  • 15. Linear Regression/1. Linear Regression Theory.mp4 9.0 MB
  • 1. Course Introduction/2. Course Help and Welcome.mp4 8.7 MB
  • 23. Recommender Systems/1. Recommender Systems.mp4 8.3 MB
  • 25. Neural Nets and Deep Learning/21. TensorFlow 2.0 Project Options Overview.mp4 8.2 MB
  • 7. Python for Data Analysis - Pandas Exercises/4. Ecommerce Purchases Exercise Overview.mp4 7.8 MB
  • 14. Introduction to Machine Learning/1. Welcome to the Machine Learning Section!.mp4 7.6 MB
  • 7. Python for Data Analysis - Pandas Exercises/2. SF Salaries Exercise Overview.mp4 7.1 MB
  • 24. Natural Language Processing/5. NLP Project Overview.mp4 7.0 MB
  • 9. Python for Data Visualization - Seaborn/8. Seaborn Exercise Overview.mp4 6.9 MB
  • 22. Principal Component Analysis/1. Principal Component Analysis.mp4 6.5 MB
  • 8. Python for Data Visualization - Matplotlib/6. Matplotlib Exercises Overview.mp4 6.1 MB
  • 17. Logistic Regression/5. Logistic Regression Project Overview.mp4 5.6 MB
  • 26. Big Data and Spark with Python/1. Welcome to the Big Data Section!.mp4 5.5 MB
  • 8. Python for Data Visualization - Matplotlib/1. Welcome to the Data Visualization Section!.mp4 5.4 MB
  • 10. Python for Data Visualization - Pandas Built-in Data Visualization/2. Pandas Data Visualization Exercise.mp4 5.4 MB
  • 18. K Nearest Neighbors/3. KNN Project Overview.mp4 5.2 MB
  • 25. Neural Nets and Deep Learning/2. Welcome to the Deep Learning Section!.mp4 5.2 MB
  • 5. Python for Data Analysis - NumPy/2. Introduction to Numpy.mp4 4.4 MB
  • 13. Data Capstone Project/1. Welcome to the Data Capstone Projects!.mp4 4.2 MB
  • 4. Python Crash Course/1. Welcome to the Python Crash Course Section!.mp4 4.2 MB
  • 6. Python for Data Analysis - Pandas/1. Welcome to the Pandas Section!.mp4 3.4 MB
  • 6. Python for Data Analysis - Pandas/2. Introduction to Pandas.mp4 3.3 MB
  • 14. Introduction to Machine Learning/2.2 Python DS Presentations.zip.zip 2.9 MB
  • 4. Python Crash Course/2. Introduction to Python Crash Course.mp4 2.8 MB
  • 5. Python for Data Analysis - NumPy/1. Welcome to the NumPy Section!.mp4 2.6 MB
  • 12. Python for Data Visualization - Geographical Plotting/1. Introduction to Geographical Plotting.mp4 2.0 MB
  • 26. Big Data and Spark with Python/9. PySpark Setup.srt 37.3 kB
  • 26. Big Data and Spark with Python/12. RDD Transformations and Actions.srt 33.1 kB
  • 25. Neural Nets and Deep Learning/30. Tensorboard.srt 31.6 kB
  • 25. Neural Nets and Deep Learning/23. Keras Project Solutions - Dealing with Missing Data.srt 30.9 kB
  • 25. Neural Nets and Deep Learning/9. Cost Functions and Gradient Descent.srt 29.2 kB
  • 11. Python for Data Visualization - Plotly and Cufflinks/2. Plotly and Cufflinks.srt 28.4 kB
  • 4. Python Crash Course/3. Python Crash Course - Part 1.srt 27.9 kB
  • 25. Neural Nets and Deep Learning/15. TF Regression Code Along - Exploratory Data Analysis.srt 27.9 kB
  • 14. Introduction to Machine Learning/4. Evaluating Performance - Classification Error Metrics.srt 27.7 kB
  • 24. Natural Language Processing/6. NLP Project Solutions.srt 27.6 kB
  • 25. Neural Nets and Deep Learning/26. Keras Project Solutions - Data PreProcessing.srt 27.4 kB
  • 18. K Nearest Neighbors/2. KNN with Python.srt 27.3 kB
  • 25. Neural Nets and Deep Learning/20. TF Classification - Dealing with Overfitting and Evaluation.srt 27.0 kB
  • 12. Python for Data Visualization - Geographical Plotting/2. Choropleth Maps - Part 1 - USA.srt 26.9 kB
  • 17. Logistic Regression/2. Logistic Regression with Python - Part 1.srt 26.8 kB
  • 15. Linear Regression/6. Linear Regression Project Solution.srt 26.7 kB
  • 15. Linear Regression/3. Linear Regression with Python - Part 1.srt 26.7 kB
  • 9. Python for Data Visualization - Seaborn/3. Categorical Plots.srt 26.6 kB
  • 26. Big Data and Spark with Python/7. EC2 Instance Set-Up.srt 26.4 kB
  • 24. Natural Language Processing/3. NLP with Python - Part 2.srt 25.9 kB
  • 13. Data Capstone Project/8. Finance Project - Solutions Part 2.srt 25.9 kB
  • 5. Python for Data Analysis - NumPy/5. Numpy Array Indexing.srt 25.7 kB
  • 8. Python for Data Visualization - Matplotlib/3. Matplotlib Part 1.srt 25.7 kB
  • 6. Python for Data Analysis - Pandas/5. DataFrames - Part 2.srt 25.6 kB
  • 20. Support Vector Machines/2. Support Vector Machines with Python.srt 25.4 kB
  • 13. Data Capstone Project/7. Finance Project - Solutions Part 1.srt 24.9 kB
  • 24. Natural Language Processing/4. NLP with Python - Part 3.srt 24.5 kB
  • 5. Python for Data Analysis - NumPy/8. Numpy Exercises Solutions.srt 24.4 kB
  • 17. Logistic Regression/3. Logistic Regression with Python - Part 2.srt 24.4 kB
  • 22. Principal Component Analysis/2. PCA with Python.srt 24.1 kB
  • 4. Python Crash Course/5. Python Crash Course - Part 3.srt 23.8 kB
  • 3. Jupyter Overview/2. Jupyter Notebooks.srt 23.3 kB
  • 21. K Means Clustering/4. K Means Project Solutions.srt 23.2 kB
  • 4. Python Crash Course/4. Python Crash Course - Part 2.srt 23.1 kB
  • 24. Natural Language Processing/2. NLP with Python - Part 1.srt 22.6 kB
  • 25. Neural Nets and Deep Learning/24. Keras Project Solutions - Dealing with Missing Data - Part Two.srt 22.4 kB
  • 8. Python for Data Visualization - Matplotlib/4. Matplotlib Part 2.srt 22.0 kB
  • 25. Neural Nets and Deep Learning/13. TF Syntax Basics - Part Two - Creating and Training the Model.srt 22.0 kB
  • 25. Neural Nets and Deep Learning/10. Backpropagation.srt 22.0 kB
  • 4. Python Crash Course/6. Python Crash Course - Part 4.srt 21.9 kB
  • 7. Python for Data Analysis - Pandas Exercises/5. Ecommerce Purchases Exercise Solutions.srt 21.9 kB
  • 6. Python for Data Analysis - Pandas/4. DataFrames - Part 1.srt 21.8 kB
  • 6. Python for Data Analysis - Pandas/11. Data Input and Output.srt 21.5 kB
  • 13. Data Capstone Project/3. 911 Calls Solutions - Part 1.srt 21.4 kB
  • 10. Python for Data Visualization - Pandas Built-in Data Visualization/1. Pandas Built-in Data Visualization.srt 21.3 kB
  • 7. Python for Data Analysis - Pandas Exercises/3. SF Salaries Solutions.srt 21.2 kB
  • 19. Decision Trees and Random Forests/2. Decision Trees and Random Forest with Python.srt 20.6 kB
  • 2. Environment Set-Up/1. Python Environment Setup.srt 20.5 kB
  • 25. Neural Nets and Deep Learning/16. TF Regression Code Along - Exploratory Data Analysis - Continued.srt 20.0 kB
  • 23. Recommender Systems/2. Recommender Systems with Python - Part 1.srt 19.9 kB
  • 18. K Nearest Neighbors/4. KNN Project Solutions.srt 19.7 kB
  • 25. Neural Nets and Deep Learning/14. TF Syntax Basics - Part Three - Model Evaluation.srt 18.9 kB
  • 25. Neural Nets and Deep Learning/25. Keras Project Solutions - Categorical Data.srt 18.8 kB
  • 6. Python for Data Analysis - Pandas/10. Operations.srt 18.2 kB
  • 8. Python for Data Visualization - Matplotlib/5. Matplotlib Part 3.srt 18.1 kB
  • 21. K Means Clustering/2. K Means with Python.srt 17.8 kB
  • 17. Logistic Regression/1. Logistic Regression Theory.srt 17.7 kB
  • 25. Neural Nets and Deep Learning/18. TF Regression Code Along - Model Evaluation and Predictions.srt 17.7 kB
  • 19. Decision Trees and Random Forests/4. Decision Trees and Random Forest Solutions Part 1.srt 17.6 kB
  • 25. Neural Nets and Deep Learning/8. Multi-Class Classification Considerations.srt 17.5 kB
  • 23. Recommender Systems/3. Recommender Systems with Python - Part 2.srt 17.5 kB
  • 25. Neural Nets and Deep Learning/7. Activation Functions.srt 17.4 kB
  • 4. Python Crash Course/8. Python Crash Course Exercises - Solutions.srt 16.8 kB
  • 25. Neural Nets and Deep Learning/12. TF Syntax Basics - Part One - Preparing the Data.srt 16.7 kB
  • 25. Neural Nets and Deep Learning/5. Perceptron Model.srt 15.8 kB
  • 3. Jupyter Overview/3. Optional Virtual Environments.srt 15.8 kB
  • 25. Neural Nets and Deep Learning/29. Keras Project Solutions - Model Evaluation.srt 15.2 kB
  • 17. Logistic Regression/6. Logistic Regression Project Solutions.srt 15.1 kB
  • 9. Python for Data Visualization - Seaborn/4. Matrix Plots.srt 14.9 kB
  • 14. Introduction to Machine Learning/6. Machine Learning with Python.srt 14.5 kB
  • 12. Python for Data Visualization - Geographical Plotting/5. Choropleth Exercises - Solutions.srt 14.2 kB
  • 6. Python for Data Analysis - Pandas/9. Merging Joining and Concatenating.srt 14.0 kB
  • 26. Big Data and Spark with Python/3. Spark Overview.srt 13.9 kB
  • 25. Neural Nets and Deep Learning/22. TensorFlow 2.0 Project Notebook Overview.srt 13.8 kB
  • 14. Introduction to Machine Learning/3. Supervised Learning Overview.srt 13.7 kB
  • 10. Python for Data Visualization - Pandas Built-in Data Visualization/3. Pandas Data Visualization Exercise- Solutions.srt 13.6 kB
  • 20. Support Vector Machines/4. SVM Project Solutions.srt 13.5 kB
  • 25. Neural Nets and Deep Learning/17. TF Regression Code Along - Data Preprocessing and Creating a Model.srt 13.4 kB
  • 8. Python for Data Visualization - Matplotlib/7. Matplotlib Exercises - Solutions.srt 13.2 kB
  • 9. Python for Data Visualization - Seaborn/5. Grids.srt 13.0 kB
  • 6. Python for Data Analysis - Pandas/6. DataFrames - Part 3.srt 12.8 kB
  • 9. Python for Data Visualization - Seaborn/7. Style and Color.srt 12.5 kB
  • 26. Big Data and Spark with Python/11. Introduction to Spark and Python.srt 12.4 kB
  • 19. Decision Trees and Random Forests/5. Decision Trees and Random Forest Solutions Part 2.srt 12.4 kB
  • 17. Logistic Regression/4. Logistic Regression with Python - Part 3.srt 12.0 kB
  • 25. Neural Nets and Deep Learning/19. TF Classification Code Along - EDA and Preprocessing.srt 12.0 kB
  • 25. Neural Nets and Deep Learning/6. Neural Networks.srt 11.8 kB
  • 5. Python for Data Analysis - NumPy/6. Numpy Operations.srt 11.1 kB
  • 9. Python for Data Visualization - Seaborn/6. Regression Plots.srt 10.5 kB
  • 9. Python for Data Visualization - Seaborn/9. Seaborn Exercise Solutions.srt 10.4 kB
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