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Udemy - Machine Learning A-Z™ Hands-On Python & R In Data Science

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Udemy - Machine Learning A-Z™ Hands-On Python & R In Data Science (Size: 5.93 GB)
  1. Welcome to the course!
  1. Applications of Machine Learning.mp4 7.99 MB
  1. Applications of Machine Learning.srt 5.3 KB
  10. Installing R and R Studio (Mac, Linux & Windows).mp4 17.56 MB
  10. Installing R and R Studio (Mac, Linux & Windows).srt 9.15 KB
  11. BONUS Meet your instructors.html 1.04 KB
  12. Some Additional Resources.html 551 B
  13. FAQBot!.html 1.76 KB
  2. BONUS Learning Paths.html 2.37 KB
  3. Why Machine Learning is the Future.mp4 12.81 MB
  3. Why Machine Learning is the Future.srt 9.23 KB
  4. Important notes, tips & tricks for this course.html 3.24 KB
  5. This PDF resource will help you a lot.html 1.49 KB
  5.1 Machine_Learning_A_Z_Q_A.pdf.pdf 2.26 MB
  6. The whole code folder of the course.html 1.02 KB
  6.1 Machine_Learning_A-Z_New.zip.zip 228.44 MB
  7. Updates on Udemy Reviews.mp4 52.91 MB
  7. Updates on Udemy Reviews.srt 4.04 KB
  8. Installing Python and Anaconda (Mac, Linux & Windows).mp4 19.52 MB
  8. Installing Python and Anaconda (Mac, Linux & Windows).srt 12.3 KB
  9. Update Recommended Anaconda Version.html 1.32 KB
  10. Evaluating Regression Models Performance
  1. R-Squared Intuition.mp4 8.85 MB
  1. R-Squared Intuition.srt 7.17 KB
  2. Adjusted R-Squared Intuition.mp4 19.28 MB
  2. Adjusted R-Squared Intuition.srt 14.45 KB
  3. Evaluating Regression Models Performance - Homework's Final Part.mp4 21.9 MB
  3. Evaluating Regression Models Performance - Homework's Final Part.srt 12.93 KB
  4. Interpreting Linear Regression Coefficients.mp4 24.21 MB
  4. Interpreting Linear Regression Coefficients.srt 13.32 KB
  5. Conclusion of Part 2 - Regression.html 2.91 KB
  11. -------------------- Part 3 Classification --------------------
  1. Welcome to Part 3 - Classification.html 831 B
  12. Logistic Regression
  1. Logistic Regression Intuition.mp4 29.18 MB
  1. Logistic Regression Intuition.srt 23.94 KB
  10. Logistic Regression in R - Step 2.mp4 7.85 MB
  10. Logistic Regression in R - Step 2.srt 4.35 KB
  11. Logistic Regression in R - Step 3.mp4 14.6 MB
  11. Logistic Regression in R - Step 3.srt 7.42 KB
  12. Logistic Regression in R - Step 4.mp4 6.9 MB
  12. Logistic Regression in R - Step 4.srt 3.98 KB
  13. Logistic Regression in R - Step 5.mp4 51.68 MB
  13. Logistic Regression in R - Step 5.srt 29.1 KB
  14. R Classification Template.mp4 12.47 MB
  14. R Classification Template.srt 6.7 KB
  15. Logistic Regression.html 125 B
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Logistic Regression in Python - Step 1.mp4 12.94 MB
  3. Logistic Regression in Python - Step 1.srt 8.76 KB
  4. Logistic Regression in Python - Step 2.mp4 8.24 MB
  4. Logistic Regression in Python - Step 2.srt 4.92 KB
  5. Logistic Regression in Python - Step 3.mp4 5.97 MB
  5. Logistic Regression in Python - Step 3.srt 4.1 KB
  6. Logistic Regression in Python - Step 4.mp4 10.37 MB
  6. Logistic Regression in Python - Step 4.srt 7.16 KB
  7. Logistic Regression in Python - Step 5.mp4 42.55 MB
  7. Logistic Regression in Python - Step 5.srt 29.7 KB
  8. Python Classification Template.mp4 12.07 MB
  8. Python Classification Template.srt 6.07 KB
  9. Logistic Regression in R - Step 1.mp4 12.59 MB
  9. Logistic Regression in R - Step 1.srt 8.92 KB
  13. K-Nearest Neighbors (K-NN)
  1. K-Nearest Neighbor Intuition.mp4 9.27 MB
  1. K-Nearest Neighbor Intuition.srt 8.04 KB
  2. How to get the dataset.mp4 11.72 MB
  2. How to get the dataset.srt 4.76 KB
  3. K-NN in Python.mp4 35.22 MB
  3. K-NN in Python.srt 21.23 KB
  4. K-NN in R.mp4 41.37 MB
  4. K-NN in R.srt 23.37 KB
  5. K-Nearest Neighbor.html 125 B
  14. Support Vector Machine (SVM)
  1. SVM Intuition.mp4 18.01 MB
  1. SVM Intuition.srt 15.72 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. SVM in Python.mp4 31.17 MB
  3. SVM in Python.srt 19.15 KB
  4. SVM in R.mp4 32.26 MB
  4. SVM in R.srt 18.4 KB
  4.1 SVM.zip.zip 8.27 KB
  15. Kernel SVM
  1. Kernel SVM Intuition.mp4 5.79 MB
  1. Kernel SVM Intuition.srt 4.41 KB
  2. Mapping to a higher dimension.mp4 13.75 MB
  2. Mapping to a higher dimension.srt 10.54 KB
  3. The Kernel Trick.mp4 29.28 MB
  3. The Kernel Trick.srt 16.52 KB
  4. Types of Kernel Functions.mp4 12.3 MB
  4. Types of Kernel Functions.srt 4.94 KB
  5. How to get the dataset.mp4 11.71 MB
  5. How to get the dataset.srt 4.76 KB
  6. Kernel SVM in Python.mp4 41.62 MB
  6. Kernel SVM in Python.srt 28.24 KB
  7. Kernel SVM in R.mp4 40.45 MB
  7. Kernel SVM in R.srt 25.44 KB
  16. Naive Bayes
  1. Bayes Theorem.mp4 43.9 MB
  1. Bayes Theorem.srt 34.45 KB
  2. Naive Bayes Intuition.mp4 27.8 MB
  2. Naive Bayes Intuition.srt 23.34 KB
  3. Naive Bayes Intuition (Challenge Reveal).mp4 13.28 MB
  3. Naive Bayes Intuition (Challenge Reveal).srt 9.5 KB
  4. Naive Bayes Intuition (Extras).mp4 18.95 MB
  4. Naive Bayes Intuition (Extras).srt 15.93 KB
  5. How to get the dataset.mp4 11.71 MB
  5. How to get the dataset.srt 4.76 KB
  6. Naive Bayes in Python.mp4 23.38 MB
  6. Naive Bayes in Python.srt 13.75 KB
  7. Naive Bayes in R.mp4 37.31 MB
  7. Naive Bayes in R.srt 21.9 KB
  17. Decision Tree Classification
  1. Decision Tree Classification Intuition.mp4 18.79 MB
  1. Decision Tree Classification Intuition.srt 12.87 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Decision Tree Classification in Python.mp4 29.81 MB
  3. Decision Tree Classification in Python.srt 19.43 KB
  4. Decision Tree Classification in R.mp4 51.18 MB
  4. Decision Tree Classification in R.srt 29.14 KB
  18. Random Forest Classification
  1. Random Forest Classification Intuition.mp4 19.43 MB
  1. Random Forest Classification Intuition.srt 7.05 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Random Forest Classification in Python.mp4 47.16 MB
  3. Random Forest Classification in Python.srt 30.73 KB
  4. Random Forest Classification in R.mp4 49.39 MB
  4. Random Forest Classification in R.srt 32.4 KB
  19. Evaluating Classification Models Performance
  1. False Positives & False Negatives.mp4 13.65 MB
  1. False Positives & False Negatives.srt 11.29 KB
  2. Confusion Matrix.mp4 8.22 MB
  2. Confusion Matrix.srt 7.51 KB
  3. Accuracy Paradox.mp4 3.8 MB
  3. Accuracy Paradox.srt 3.24 KB
  4. CAP Curve.mp4 18.68 MB
  4. CAP Curve.srt 16.18 KB
  5. CAP Curve Analysis.mp4 11.52 MB
  5. CAP Curve Analysis.srt 9.24 KB
  6. Conclusion of Part 3 - Classification.html 3.47 KB
  2. -------------------- Part 1 Data Preprocessing --------------------
  1. Welcome to Part 1 - Data Preprocessing.mp4 2.98 MB
  1. Welcome to Part 1 - Data Preprocessing.srt 2.52 KB
  10. Feature Scaling.mp4 34.63 MB
  10. Feature Scaling.srt 23.47 KB
  11. And here is our Data Preprocessing Template!.mp4 19.67 MB
  11. And here is our Data Preprocessing Template!.srt 14.15 KB
  12. Data Preprocessing.html 125 B
  2. Get the dataset.mp4 21.16 MB
  2. Get the dataset.srt 10.69 KB
  3. Importing the Libraries.mp4 11.07 MB
  3. Importing the Libraries.srt 8.06 KB
  4. Importing the Dataset.mp4 23.32 MB
  4. Importing the Dataset.srt 18.66 KB
  5. For Python learners, summary of Object-oriented programming classes & objects.html 1.58 KB
  6. Missing Data.mp4 32.17 MB
  6. Missing Data.srt 22.67 KB
  7. Categorical Data.mp4 40.79 MB
  7. Categorical Data.srt 27.01 KB
  8. WARNING - Update.html 2.86 KB
  9. Splitting the Dataset into the Training set and Test set.mp4 39.04 MB
  9. Splitting the Dataset into the Training set and Test set.srt 26.91 KB
  20. -------------------- Part 4 Clustering --------------------
  1. Welcome to Part 4 - Clustering.html 734 B
  21. K-Means Clustering
  1. K-Means Clustering Intuition.mp4 26.86 MB
  1. K-Means Clustering Intuition.srt 23.34 KB
  2. K-Means Random Initialization Trap.mp4 15.36 MB
  2. K-Means Random Initialization Trap.srt 12.95 KB
  3. K-Means Selecting The Number Of Clusters.mp4 23.14 MB
  3. K-Means Selecting The Number Of Clusters.srt 18.46 KB
  4. How to get the dataset.mp4 11.71 MB
  4. How to get the dataset.srt 4.76 KB
  5. K-Means Clustering in Python.mp4 39.77 MB
  5. K-Means Clustering in Python.srt 28.23 KB
  6. K-Means Clustering in R.mp4 28.99 MB
  6. K-Means Clustering in R.srt 19.44 KB
  7. K-Means Clustering.html 125 B
  22. Hierarchical Clustering
  1. Hierarchical Clustering Intuition.mp4 16.52 MB
  1. Hierarchical Clustering Intuition.srt 14.59 KB
  10. HC in R - Step 1.mp4 7.38 MB
  10. HC in R - Step 1.srt 6.35 KB
  11. HC in R - Step 2.mp4 11.15 MB
  11. HC in R - Step 2.srt 8.14 KB
  12. HC in R - Step 3.mp4 7.81 MB
  12. HC in R - Step 3.srt 4.73 KB
  13. HC in R - Step 4.mp4 7.45 MB
  13. HC in R - Step 4.srt 3.83 KB
  14. HC in R - Step 5.mp4 6.88 MB
  14. HC in R - Step 5.srt 4.03 KB
  15. Hierarchical Clustering.html 125 B
  16. Conclusion of Part 4 - Clustering.html 516 B
  16.1 Clustering-Pros-Cons.pdf.pdf 25.76 KB
  2. Hierarchical Clustering How Dendrograms Work.mp4 17.46 MB
  2. Hierarchical Clustering How Dendrograms Work.srt 14.35 KB
  3. Hierarchical Clustering Using Dendrograms.mp4 22.82 MB
  3. Hierarchical Clustering Using Dendrograms.srt 17.6 KB
  4. How to get the dataset.mp4 11.71 MB
  4. How to get the dataset.srt 4.76 KB
  5. HC in Python - Step 1.mp4 10.72 MB
  5. HC in Python - Step 1.srt 7.59 KB
  6. HC in Python - Step 2.mp4 12.65 MB
  6. HC in Python - Step 2.srt 9.51 KB
  7. HC in Python - Step 3.mp4 12.31 MB
  7. HC in Python - Step 3.srt 7.72 KB
  8. HC in Python - Step 4.mp4 12.03 MB
  8. HC in Python - Step 4.srt 6.46 KB
  9. HC in Python - Step 5.mp4 8.39 MB
  9. HC in Python - Step 5.srt 6.79 KB
  23. -------------------- Part 5 Association Rule Learning --------------------
  1. Welcome to Part 5 - Association Rule Learning.html 425 B
  24. Apriori
  1. Apriori Intuition.mp4 35.02 MB
  1. Apriori Intuition.srt 25.91 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Apriori in R - Step 1.mp4 42.87 MB
  3. Apriori in R - Step 1.srt 31.05 KB
  4. Apriori in R - Step 2.mp4 30.51 MB
  4. Apriori in R - Step 2.srt 23.02 KB
  5. Apriori in R - Step 3.mp4 43.84 MB
  5. Apriori in R - Step 3.srt 31.16 KB
  6. Apriori in Python - Step 1.mp4 37.98 MB
  6. Apriori in Python - Step 1.srt 27.96 KB
  7. Apriori in Python - Step 2.mp4 29.52 MB
  7. Apriori in Python - Step 2.srt 22.53 KB
  8. Apriori in Python - Step 3.mp4 26.96 MB
  8. Apriori in Python - Step 3.srt 19.6 KB
  25. Eclat
  1. Eclat Intuition.mp4 10.65 MB
  1. Eclat Intuition.srt 8.1 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Eclat in R.mp4 20.68 MB
  3. Eclat in R.srt 15.79 KB
  3.1 Eclat.zip.zip 48.54 KB
  26. -------------------- Part 6 Reinforcement Learning --------------------
  1. Welcome to Part 6 - Reinforcement Learning.html 804 B
  27. Upper Confidence Bound (UCB)
  1. The Multi-Armed Bandit Problem.mp4 30.19 MB
  1. The Multi-Armed Bandit Problem.srt 22.27 KB
  10. Upper Confidence Bound in R - Step 3.mp4 47.2 MB
  10. Upper Confidence Bound in R - Step 3.srt 25.32 KB
  11. Upper Confidence Bound in R - Step 4.mp4 7.4 MB
  11. Upper Confidence Bound in R - Step 4.srt 4.41 KB
  2. Upper Confidence Bound (UCB) Intuition.mp4 29.32 MB
  2. Upper Confidence Bound (UCB) Intuition.srt 21.92 KB
  3. How to get the dataset.mp4 11.71 MB
  3. How to get the dataset.srt 4.76 KB
  4. Upper Confidence Bound in Python - Step 1.mp4 31.54 MB
  4. Upper Confidence Bound in Python - Step 1.srt 21.86 KB
  5. Upper Confidence Bound in Python - Step 2.mp4 35.44 MB
  5. Upper Confidence Bound in Python - Step 2.srt 25.26 KB
  6. Upper Confidence Bound in Python - Step 3.mp4 41.11 MB
  6. Upper Confidence Bound in Python - Step 3.srt 26.94 KB
  7. Upper Confidence Bound in Python - Step 4.mp4 9.13 MB
  7. Upper Confidence Bound in Python - Step 4.srt 4.99 KB
  8. Upper Confidence Bound in R - Step 1.mp4 28.05 MB
  8. Upper Confidence Bound in R - Step 1.srt 20.54 KB
  9. Upper Confidence Bound in R - Step 2.mp4 29.01 MB
  9. Upper Confidence Bound in R - Step 2.srt 22.17 KB
  28. Thompson Sampling
  1. Thompson Sampling Intuition.mp4 37.27 MB
  1. Thompson Sampling Intuition.srt 27.53 KB
  2. Algorithm Comparison UCB vs Thompson Sampling.mp4 14.09 MB
  2. Algorithm Comparison UCB vs Thompson Sampling.srt 11.14 KB
  3. How to get the dataset.mp4 11.71 MB
  3. How to get the dataset.srt 4.76 KB
  4. Thompson Sampling in Python - Step 1.mp4 43.13 MB
  4. Thompson Sampling in Python - Step 1.srt 28.88 KB
  5. Thompson Sampling in Python - Step 2.mp4 8.41 MB
  5. Thompson Sampling in Python - Step 2.srt 5.8 KB
  6. Thompson Sampling in R - Step 1.mp4 40.93 MB
  6. Thompson Sampling in R - Step 1.srt 27.86 KB
  7. Thompson Sampling in R - Step 2.mp4 7.47 MB
  7. Thompson Sampling in R - Step 2.srt 5.29 KB
  29. -------------------- Part 7 Natural Language Processing --------------------
  1. Welcome to Part 7 - Natural Language Processing.html 1.69 KB
  10. Natural Language Processing in Python - Step 7.mp4 17.1 MB
  10. Natural Language Processing in Python - Step 7.srt 9.8 KB
  11. Natural Language Processing in Python - Step 8.mp4 39.48 MB
  11. Natural Language Processing in Python - Step 8.srt 23.79 KB
  12. Natural Language Processing in Python - Step 9.mp4 14.02 MB
  12. Natural Language Processing in Python - Step 9.srt 8.25 KB
  13. Natural Language Processing in Python - Step 10.mp4 24.13 MB
  13. Natural Language Processing in Python - Step 10.srt 14.38 KB
  14. Homework Challenge.html 1.37 KB
  15. Natural Language Processing in R - Step 1.mp4 40.37 MB
  15. Natural Language Processing in R - Step 1.srt 24 KB
  16. Natural Language Processing in R - Step 2.mp4 17.47 MB
  16. Natural Language Processing in R - Step 2.srt 12.88 KB
  17. Natural Language Processing in R - Step 3.mp4 13.52 MB
  17. Natural Language Processing in R - Step 3.srt 10.12 KB
  18. Natural Language Processing in R - Step 4.mp4 6.5 MB
  18. Natural Language Processing in R - Step 4.srt 4.66 KB
  19. Natural Language Processing in R - Step 5.mp4 4.57 MB
  19. Natural Language Processing in R - Step 5.srt 3.25 KB
  2. Natural Language Processing Intuition.mp4 29.69 MB
  2. Natural Language Processing Intuition.srt 7.07 KB
  20. Natural Language Processing in R - Step 6.mp4 12.74 MB
  20. Natural Language Processing in R - Step 6.srt 8.35 KB
  21. Natural Language Processing in R - Step 7.mp4 7.52 MB
  21. Natural Language Processing in R - Step 7.srt 5.59 KB
  22. Natural Language Processing in R - Step 8.mp4 13.27 MB
  22. Natural Language Processing in R - Step 8.srt 8.01 KB
  23. Natural Language Processing in R - Step 9.mp4 29 MB
  23. Natural Language Processing in R - Step 9.srt 19.6 KB
  24. Natural Language Processing in R - Step 10.mp4 41.19 MB
  24. Natural Language Processing in R - Step 10.srt 26.29 KB
  25. Homework Challenge.html 1.4 KB
  3. How to get the dataset.mp4 11.71 MB
  3. How to get the dataset.srt 4.76 KB
  4. Natural Language Processing in Python - Step 1.mp4 35.2 MB
  4. Natural Language Processing in Python - Step 1.srt 18.33 KB
  5. Natural Language Processing in Python - Step 2.mp4 21.96 MB
  5. Natural Language Processing in Python - Step 2.srt 15.79 KB
  6. Natural Language Processing in Python - Step 3.mp4 3.38 MB
  6. Natural Language Processing in Python - Step 3.srt 2.6 KB
  7. Natural Language Processing in Python - Step 4.mp4 24.01 MB
  7. Natural Language Processing in Python - Step 4.srt 17.48 KB
  8. Natural Language Processing in Python - Step 5.mp4 14.9 MB
  8. Natural Language Processing in Python - Step 5.srt 10.66 KB
  9. Natural Language Processing in Python - Step 6.mp4 6.49 MB
  9. Natural Language Processing in Python - Step 6.srt 4.39 KB
  3. -------------------- Part 2 Regression --------------------
  1. Welcome to Part 2 - Regression.html 875 B
  30. -------------------- Part 8 Deep Learning --------------------
  1. Welcome to Part 8 - Deep Learning.html 870 B
  2. What is Deep Learning.mp4 31.31 MB
  2. What is Deep Learning.srt 18.13 KB
  31. Artificial Neural Networks
  1. Plan of attack.mp4 4.74 MB
  1. Plan of attack.srt 4 KB
  10. Business Problem Description.mp4 16.37 MB
  10. Business Problem Description.srt 7.3 KB
  11. Installing Keras.html 1.42 KB
  12. ANN in Python - Step 1.mp4 29.31 MB
  12. ANN in Python - Step 1.srt 20.01 KB
  13. ANN in Python - Step 2.mp4 48.1 MB
  13. ANN in Python - Step 2.srt 28.95 KB
  14. ANN in Python - Step 3.mp4 8.37 MB
  14. ANN in Python - Step 3.srt 5.18 KB
  15. ANN in Python - Step 4.mp4 5.88 MB
  15. ANN in Python - Step 4.srt 3.86 KB
  16. ANN in Python - Step 5.mp4 29.59 MB
  16. ANN in Python - Step 5.srt 19.49 KB
  17. ANN in Python - Step 6.mp4 7.05 MB
  17. ANN in Python - Step 6.srt 4.5 KB
  18. ANN in Python - Step 7.mp4 8.99 MB
  18. ANN in Python - Step 7.srt 5.68 KB
  19. ANN in Python - Step 8.mp4 18.16 MB
  19. ANN in Python - Step 8.srt 11.07 KB
  2. The Neuron.mp4 29.87 MB
  2. The Neuron.srt 25.04 KB
  20. ANN in Python - Step 9.mp4 16.89 MB
  20. ANN in Python - Step 9.srt 9.51 KB
  21. ANN in Python - Step 10.mp4 17.09 MB
  21. ANN in Python - Step 10.srt 10.35 KB
  22. ANN in R - Step 1.mp4 38.56 MB
  22. ANN in R - Step 1.srt 26.79 KB
  23. ANN in R - Step 2.mp4 14.18 MB
  23. ANN in R - Step 2.srt 10.12 KB
  24. ANN in R - Step 3.mp4 28.95 MB
  24. ANN in R - Step 3.srt 18.88 KB
  25. ANN in R - Step 4 (Last step).mp4 33.45 MB
  25. ANN in R - Step 4 (Last step).srt 20.68 KB
  3. The Activation Function.mp4 14.76 MB
  3. The Activation Function.srt 12.03 KB
  4. How do Neural Networks work.mp4 23.54 MB
  4. How do Neural Networks work.srt 19.11 KB
  5. How do Neural Networks learn.mp4 26.55 MB
  5. How do Neural Networks learn.srt 18.95 KB
  6. Gradient Descent.mp4 18.54 MB
  6. Gradient Descent.srt 14.02 KB
  7. Stochastic Gradient Descent.mp4 16.82 MB
  7. Stochastic Gradient Descent.srt 12.14 KB
  8. Backpropagation.mp4 10.92 MB
  8. Backpropagation.srt 7.11 KB
  9. How to get the dataset.mp4 11.71 MB
  9. How to get the dataset.srt 4.76 KB
  32. Convolutional Neural Networks
  1. Plan of attack.mp4 5.9 MB
  1. Plan of attack.srt 5.24 KB
  10. How to get the dataset.mp4 11.71 MB
  10. How to get the dataset.srt 4.76 KB
  11. Installing Keras.html 927 B
  12. CNN in Python - Step 1.mp4 24.92 MB
  12. CNN in Python - Step 1.srt 18.37 KB
  13. CNN in Python - Step 2.mp4 5.85 MB
  13. CNN in Python - Step 2.srt 4.46 KB
  14. CNN in Python - Step 3.mp4 2.22 MB
  14. CNN in Python - Step 3.srt 1.71 KB
  15. CNN in Python - Step 4.mp4 27.18 MB
  15. CNN in Python - Step 4.srt 19.28 KB
  16. CNN in Python - Step 5.mp4 9.91 MB
  16. CNN in Python - Step 5.srt 7.48 KB
  17. CNN in Python - Step 6.mp4 9.7 MB
  17. CNN in Python - Step 6.srt 7.6 KB
  18. CNN in Python - Step 7.mp4 12.93 MB
  18. CNN in Python - Step 7.srt 9.12 KB
  19. CNN in Python - Step 8.mp4 6.79 MB
  19. CNN in Python - Step 8.srt 4.57 KB
  2. What are convolutional neural networks.mp4 29.51 MB
  2. What are convolutional neural networks.srt 22.06 KB
  20. CNN in Python - Step 9.mp4 46.85 MB
  20. CNN in Python - Step 9.srt 29.38 KB
  21. CNN in Python - Step 10.mp4 20.61 MB
  21. CNN in Python - Step 10.srt 12.97 KB
  22. CNN in R.html 2.38 KB
  3. Step 1 - Convolution Operation.mp4 31.03 MB
  3. Step 1 - Convolution Operation.srt 23.23 KB
  4. Step 1(b) - ReLU Layer.mp4 14.1 MB
  4. Step 1(b) - ReLU Layer.srt 9.2 KB
  5. Step 2 - Pooling.mp4 40.24 MB
  5. Step 2 - Pooling.srt 21.04 KB
  6. Step 3 - Flattening.mp4 3.27 MB
  6. Step 3 - Flattening.srt 2.54 KB
  7. Step 4 - Full Connection.mp4 42.75 MB
  7. Step 4 - Full Connection.srt 28.57 KB
  8. Summary.mp4 7.91 MB
  8. Summary.srt 6.02 KB
  9. Softmax & Cross-Entropy.mp4 33.23 MB
  9. Softmax & Cross-Entropy.srt 25.27 KB
  33. -------------------- Part 9 Dimensionality Reduction --------------------
  1. Welcome to Part 9 - Dimensionality Reduction.html 1.26 KB
  34. Principal Component Analysis (PCA)
  1. Principal Component Analysis (PCA) Intuition.mp4 32.11 MB
  1. Principal Component Analysis (PCA) Intuition.srt 5.05 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. PCA in Python - Step 1.mp4 31.96 MB
  3. PCA in Python - Step 1.srt 17.66 KB
  4. PCA in Python - Step 2.mp4 22.08 MB
  4. PCA in Python - Step 2.srt 11.81 KB
  5. PCA in Python - Step 3.mp4 25.51 MB
  5. PCA in Python - Step 3.srt 14.81 KB
  6. PCA in R - Step 1.mp4 30.66 MB
  6. PCA in R - Step 1.srt 18.7 KB
  7. PCA in R - Step 2.mp4 29.03 MB
  7. PCA in R - Step 2.srt 16.89 KB
  8. PCA in R - Step 3.mp4 36.74 MB
  8. PCA in R - Step 3.srt 19.76 KB
  35. Linear Discriminant Analysis (LDA)
  1. Linear Discriminant Analysis (LDA) Intuition.mp4 26.98 MB
  1. Linear Discriminant Analysis (LDA) Intuition.srt 5.11 KB
  2. How to get the dataset.mp4 11.72 MB
  2. How to get the dataset.srt 4.76 KB
  3. LDA in Python.mp4 45.42 MB
  3. LDA in Python.srt 26.5 KB
  4. LDA in R.mp4 51.29 MB
  4. LDA in R.srt 29.68 KB
  36. Kernel PCA
  1. How to get the dataset.mp4 11.72 MB
  1. How to get the dataset.srt 4.76 KB
  2. Kernel PCA in Python.mp4 33.38 MB
  2. Kernel PCA in Python.srt 21.48 KB
  3. Kernel PCA in R.mp4 56.57 MB
  3. Kernel PCA in R.srt 30.81 KB
  37. -------------------- Part 10 Model Selection & Boosting --------------------
  1. Welcome to Part 10 - Model Selection & Boosting.html 899 B
  38. Model Selection
  1. How to get the dataset.mp4 11.71 MB
  1. How to get the dataset.srt 4.76 KB
  2. k-Fold Cross Validation in Python.mp4 32.83 MB
  2. k-Fold Cross Validation in Python.srt 20.22 KB
  3. k-Fold Cross Validation in R.mp4 43.63 MB
  3. k-Fold Cross Validation in R.srt 27.91 KB
  4. Grid Search in Python - Step 1.mp4 38.21 MB
  4. Grid Search in Python - Step 1.srt 22.05 KB
  5. Grid Search in Python - Step 2.mp4 29.52 MB
  5. Grid Search in Python - Step 2.srt 15.32 KB
  6. Grid Search in R.mp4 35.55 MB
  6. Grid Search in R.srt 20.94 KB
  39. XGBoost
  1. How to get the dataset.mp4 11.71 MB
  1. How to get the dataset.srt 4.76 KB
  2. XGBoost in Python - Step 1.mp4 21.39 MB
  2. XGBoost in Python - Step 1.srt 13.66 KB
  3. XGBoost in Python - Step 2.mp4 31.97 MB
  3. XGBoost in Python - Step 2.srt 18.89 KB
  4. XGBoost in R.mp4 47.27 MB
  4. XGBoost in R.srt 26 KB
  5. THANK YOU bonus video.mp4 52.25 MB
  5. THANK YOU bonus video.srt 2.31 KB
  4. Simple Linear Regression
  1. How to get the dataset.mp4 11.71 MB
  1. How to get the dataset.srt 4.76 KB
  10. Simple Linear Regression in R - Step 2.mp4 14.35 MB
  10. Simple Linear Regression in R - Step 2.srt 8.89 KB
  11. Simple Linear Regression in R - Step 3.mp4 8.63 MB
  11. Simple Linear Regression in R - Step 3.srt 5.52 KB
  12. Simple Linear Regression in R - Step 4.mp4 37.37 MB
  12. Simple Linear Regression in R - Step 4.srt 23.94 KB
  13. Simple Linear Regression.html 125 B
  2. Dataset + Business Problem Description.mp4 6.62 MB
  2. Dataset + Business Problem Description.srt 4.08 KB
  3. Simple Linear Regression Intuition - Step 1.mp4 9.47 MB
  3. Simple Linear Regression Intuition - Step 1.srt 8.3 KB
  4. Simple Linear Regression Intuition - Step 2.mp4 5.37 MB
  4. Simple Linear Regression Intuition - Step 2.srt 4.34 KB
  5. Simple Linear Regression in Python - Step 1.mp4 21.72 MB
  5. Simple Linear Regression in Python - Step 1.srt 15.46 KB
  6. Simple Linear Regression in Python - Step 2.mp4 18.75 MB
  6. Simple Linear Regression in Python - Step 2.srt 12.32 KB
  7. Simple Linear Regression in Python - Step 3.mp4 15.61 MB
  7. Simple Linear Regression in Python - Step 3.srt 9.84 KB
  8. Simple Linear Regression in Python - Step 4.mp4 30.83 MB
  8. Simple Linear Regression in Python - Step 4.srt 22.44 KB
  9. Simple Linear Regression in R - Step 1.mp4 9.53 MB
  9. Simple Linear Regression in R - Step 1.srt 7.71 KB
  40. Bonus Lectures
  1. YOUR SPECIAL BONUS.html 4.69 KB
  5. Multiple Linear Regression
  1. How to get the dataset.mp4 11.71 MB
  1. How to get the dataset.srt 4.76 KB
  10. Multiple Linear Regression in Python - Step 2.mp4 7.22 MB
  10. Multiple Linear Regression in Python - Step 2.srt 4.07 KB
  11. Multiple Linear Regression in Python - Step 3.mp4 14.3 MB
  11. Multiple Linear Regression in Python - Step 3.srt 8.27 KB
  12. Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 23.82 MB
  12. Multiple Linear Regression in Python - Backward Elimination - Preparation.srt 14.93 KB
  13. Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.mp4 32.59 MB
  13. Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.srt 19.68 KB
  14. Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 27.17 MB
  14. Multiple Linear Regression in Python - Backward Elimination - Homework Solution.srt 14.17 KB
  15. Multiple Linear Regression in Python - Automatic Backward Elimination.html 2.14 KB
  16. Multiple Linear Regression in R - Step 1.mp4 17.94 MB
  16. Multiple Linear Regression in R - Step 1.srt 11.85 KB
  17. Multiple Linear Regression in R - Step 2.mp4 25.93 MB
  17. Multiple Linear Regression in R - Step 2.srt 15.43 KB
  18. Multiple Linear Regression in R - Step 3.mp4 10.41 MB
  18. Multiple Linear Regression in R - Step 3.srt 7.06 KB
  19. Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.mp4 39.73 MB
  19. Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.srt 27.48 KB
  2. Dataset + Business Problem Description.mp4 9.98 MB
  2. Dataset + Business Problem Description.srt 5.68 KB
  20. Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 17.24 MB
  20. Multiple Linear Regression in R - Backward Elimination - Homework Solution.srt 11.86 KB
  21. Multiple Linear Regression in R - Automatic Backward Elimination.html 726 B
  22. Multiple Linear Regression.html 125 B
  3. Multiple Linear Regression Intuition - Step 1.mp4 1.82 MB
  3. Multiple Linear Regression Intuition - Step 1.srt 1.58 KB
  4. Multiple Linear Regression Intuition - Step 2.mp4 1.78 MB
  4. Multiple Linear Regression Intuition - Step 2.srt 1.45 KB
  5. Multiple Linear Regression Intuition - Step 3.mp4 14.29 MB
  5. Multiple Linear Regression Intuition - Step 3.srt 10.7 KB
  6. Multiple Linear Regression Intuition - Step 4.mp4 4.51 MB
  6. Multiple Linear Regression Intuition - Step 4.srt 3.51 KB
  7. Prerequisites What is the P-Value.html 676 B
  8. Multiple Linear Regression Intuition - Step 5.mp4 28.84 MB
  8. Multiple Linear Regression Intuition - Step 5.srt 23.56 KB
  9. Multiple Linear Regression in Python - Step 1.mp4 39.57 MB
  9. Multiple Linear Regression in Python - Step 1.srt 24.44 KB
  6. Polynomial Regression
  1. Polynomial Regression Intuition.mp4 9.44 MB
  1. Polynomial Regression Intuition.srt 7.82 KB
  10. Polynomial Regression in R - Step 3.mp4 43.31 MB
  10. Polynomial Regression in R - Step 3.srt 30.86 KB
  11. Polynomial Regression in R - Step 4.mp4 22.34 MB
  11. Polynomial Regression in R - Step 4.srt 15.44 KB
  12. R Regression Template.mp4 25.41 MB
  12. R Regression Template.srt 18.63 KB
  2. How to get the dataset.mp4 11.72 MB
  2. How to get the dataset.srt 4.76 KB
  3. Polynomial Regression in Python - Step 1.mp4 24.89 MB
  3. Polynomial Regression in Python - Step 1.srt 17.5 KB
  4. Polynomial Regression in Python - Step 2.mp4 27.11 MB
  4. Polynomial Regression in Python - Step 2.srt 17.21 KB
  5. Polynomial Regression in Python - Step 3.mp4 42.99 MB
  5. Polynomial Regression in Python - Step 3.srt 31.4 KB
  6. Polynomial Regression in Python - Step 4.mp4 13.51 MB
  6. Polynomial Regression in Python - Step 4.srt 8.65 KB
  7. Python Regression Template.mp4 27.43 MB
  7. Python Regression Template.srt 16.38 KB
  8. Polynomial Regression in R - Step 1.mp4 17.78 MB
  8. Polynomial Regression in R - Step 1.srt 14.12 KB
  9. Polynomial Regression in R - Step 2.mp4 23.87 MB
  9. Polynomial Regression in R - Step 2.srt 15.27 KB
  7. Support Vector Regression (SVR)
  1. How to get the dataset.mp4 11.71 MB
  1. How to get the dataset.srt 4.76 KB
  2. SVR Intuition.mp4 46.6 MB
  2. SVR Intuition.srt 11.36 KB
  3. SVR in Python.mp4 46.19 MB
  3. SVR in Python.srt 30.88 KB
  4. SVR in R.mp4 25.87 MB
  4. SVR in R.srt 18.7 KB
  8. Decision Tree Regression
  1. Decision Tree Regression Intuition.mp4 22.69 MB
  1. Decision Tree Regression Intuition.srt 17.06 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Decision Tree Regression in Python.mp4 33.54 MB
  3. Decision Tree Regression in Python.srt 23.72 KB
  4. Decision Tree Regression in R.mp4 44.37 MB
  4. Decision Tree Regression in R.srt 32.15 KB
  9. Random Forest Regression
  1. Random Forest Regression Intuition.mp4 13.82 MB
  1. Random Forest Regression Intuition.srt 10.22 KB
  2. How to get the dataset.mp4 11.71 MB
  2. How to get the dataset.srt 4.76 KB
  3. Random Forest Regression in Python.mp4 39.47 MB
  3. Random Forest Regression in Python.srt 27.53 KB
  4. Random Forest Regression in R.mp4 40.34 MB
  4. Random Forest Regression in R.srt 28.11 KB
  [FreeAllCourse.Com].URL 228 B
  ▲ 570 total files

Description


Machine Learning A-Z™ Hands-On Python & R In Data Science



Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.

What you'll learn

   Master Machine Learning on Python & R
   Have a great intuition of many Machine Learning models
   Make accurate predictions
   Make powerful analysis
   Make robust Machine Learning models
   Create strong added value to your business
   Use Machine Learning for personal purpose
   Handle specific topics like Reinforcement Learning, NLP and Deep Learning
Created by Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, SuperDataScience Support
Last updated 12/2019
English

For More Updated Courses Visit   https://freeallcourse.com/

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