DesireCourse Net Udemy Machine Learning Hands On Python In Data Science

DesireCourse Net Udemy Machine Learning Hands On Python In Data Science

Name	[DesireCourse.Net] Udemy - Machine Learning A-Z™ Hands-On Python & R In Data Science	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	6.4 GB
Total Files	575
Hash	EC385DD048F6807C9C5779F6209AF266BA3E74A3

/1. Welcome to the course!/
1. Applications of Machine Learning.mp4	8.4 MB
1. Applications of Machine Learning.srt	5.4 KB
10. Installing R and R Studio (Mac, Linux & Windows).mp4	18.4 MB
10. Installing R and R Studio (Mac, Linux & Windows).srt	9.4 KB
11. BONUS Meet your instructors.html	1.1 KB
12. Some Additional Resources.html	0.6 KB
13. FAQBot!.html	1.8 KB
2. BONUS Learning Paths.html	2.4 KB
3. Why Machine Learning is the Future.mp4	13.4 MB
3. Why Machine Learning is the Future.srt	9.5 KB
4. Important notes, tips & tricks for this course.html	3.3 KB
5. This PDF resource will help you a lot.html	1.5 KB
5.1 Machine_Learning_A_Z_Q_A.pdf.pdf	2.4 MB
6. The whole code folder of the course.html	1.0 KB
6.1 Machine_Learning_A-Z_New.zip.zip	239.5 MB
7. Updates on Udemy Reviews.mp4	55.5 MB
7. Updates on Udemy Reviews.srt	4.1 KB
8. Installing Python and Anaconda (Mac, Linux & Windows).mp4	20.5 MB
8. Installing Python and Anaconda (Mac, Linux & Windows).srt	12.6 KB
9. Update Recommended Anaconda Version.html	1.4 KB
/10. Evaluating Regression Models Performance/
1. R-Squared Intuition.mp4	9.3 MB
1. R-Squared Intuition.srt	7.3 KB
2. Adjusted R-Squared Intuition.mp4	20.2 MB
2. Adjusted R-Squared Intuition.srt	14.8 KB
3. Evaluating Regression Models Performance - Homework's Final Part.mp4	23.0 MB
3. Evaluating Regression Models Performance - Homework's Final Part.srt	13.2 KB
4. Interpreting Linear Regression Coefficients.mp4	25.4 MB
4. Interpreting Linear Regression Coefficients.srt	13.6 KB
5. Conclusion of Part 2 - Regression.html	3.0 KB
/11. -------------------- Part 3 Classification --------------------/
1. Welcome to Part 3 - Classification.html	0.8 KB
/12. Logistic Regression/
1. Logistic Regression Intuition.mp4	30.6 MB
1. Logistic Regression Intuition.srt	24.5 KB
10. Logistic Regression in R - Step 2.mp4	8.2 MB
10. Logistic Regression in R - Step 2.srt	4.5 KB
11. Logistic Regression in R - Step 3.mp4	15.3 MB
11. Logistic Regression in R - Step 3.srt	7.6 KB
12. Logistic Regression in R - Step 4.mp4	7.2 MB
12. Logistic Regression in R - Step 4.srt	4.1 KB
13. Warning - Update.html	1.4 KB
14. Logistic Regression in R - Step 5.mp4	54.2 MB
14. Logistic Regression in R - Step 5.srt	29.8 KB
15. R Classification Template.mp4	13.1 MB
15. R Classification Template.srt	6.9 KB
16. Logistic Regression.html	0.1 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Logistic Regression in Python - Step 1.mp4	13.6 MB
3. Logistic Regression in Python - Step 1.srt	9.0 KB
4. Logistic Regression in Python - Step 2.mp4	8.6 MB
4. Logistic Regression in Python - Step 2.srt	5.0 KB
5. Logistic Regression in Python - Step 3.mp4	6.3 MB
5. Logistic Regression in Python - Step 3.srt	4.2 KB
6. Logistic Regression in Python - Step 4.mp4	10.9 MB
6. Logistic Regression in Python - Step 4.srt	7.3 KB
7. Logistic Regression in Python - Step 5.mp4	44.6 MB
7. Logistic Regression in Python - Step 5.srt	30.4 KB
8. Python Classification Template.mp4	12.7 MB
8. Python Classification Template.srt	6.2 KB
9. Logistic Regression in R - Step 1.mp4	13.2 MB
9. Logistic Regression in R - Step 1.srt	9.1 KB
/13. K-Nearest Neighbors (K-NN)/
1. K-Nearest Neighbor Intuition.mp4	9.7 MB
1. K-Nearest Neighbor Intuition.srt	8.2 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. K-NN in Python.mp4	36.9 MB
3. K-NN in Python.srt	21.7 KB
4. K-NN in R.mp4	43.4 MB
4. K-NN in R.srt	23.9 KB
5. K-Nearest Neighbor.html	0.1 KB
/14. Support Vector Machine (SVM)/
1. SVM Intuition.mp4	18.9 MB
1. SVM Intuition.srt	16.1 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. SVM in Python.mp4	32.7 MB
3. SVM in Python.srt	19.6 KB
4. SVM in R.mp4	33.8 MB
4. SVM in R.srt	18.8 KB
4.1 SVM.zip.zip	8.5 KB
/15. Kernel SVM/
1. Kernel SVM Intuition.mp4	6.1 MB
1. Kernel SVM Intuition.srt	4.5 KB
2. Mapping to a higher dimension.mp4	14.4 MB
2. Mapping to a higher dimension.srt	10.8 KB
3. The Kernel Trick.mp4	30.7 MB
3. The Kernel Trick.srt	16.9 KB
4. Types of Kernel Functions.mp4	12.9 MB
4. Types of Kernel Functions.srt	5.1 KB
5. How to get the dataset.mp4	12.3 MB
5. How to get the dataset.srt	4.9 KB
6. Kernel SVM in Python.mp4	43.6 MB
6. Kernel SVM in Python.srt	28.9 KB
7. Kernel SVM in R.mp4	42.4 MB
7. Kernel SVM in R.srt	26.1 KB
/16. Naive Bayes/
1. Bayes Theorem.mp4	46.0 MB
1. Bayes Theorem.srt	35.3 KB
2. Naive Bayes Intuition.mp4	29.1 MB
2. Naive Bayes Intuition.srt	23.9 KB
3. Naive Bayes Intuition (Challenge Reveal).mp4	13.9 MB
3. Naive Bayes Intuition (Challenge Reveal).srt	9.7 KB
4. Naive Bayes Intuition (Extras).mp4	19.9 MB
4. Naive Bayes Intuition (Extras).srt	16.3 KB
5. How to get the dataset.mp4	12.3 MB
5. How to get the dataset.srt	4.9 KB
6. Naive Bayes in Python.mp4	24.5 MB
6. Naive Bayes in Python.srt	14.1 KB
7. Naive Bayes in R.mp4	39.1 MB
7. Naive Bayes in R.srt	22.4 KB
/17. Decision Tree Classification/
1. Decision Tree Classification Intuition.mp4	19.7 MB
1. Decision Tree Classification Intuition.srt	13.2 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Decision Tree Classification in Python.mp4	31.2 MB
3. Decision Tree Classification in Python.srt	19.9 KB
4. Decision Tree Classification in R.mp4	53.7 MB
4. Decision Tree Classification in R.srt	29.8 KB
/18. Random Forest Classification/
1. Random Forest Classification Intuition.mp4	20.4 MB
1. Random Forest Classification Intuition.srt	7.2 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Random Forest Classification in Python.mp4	49.4 MB
3. Random Forest Classification in Python.srt	31.5 KB
4. Random Forest Classification in R.mp4	51.8 MB
4. Random Forest Classification in R.srt	33.2 KB
/19. Evaluating Classification Models Performance/
1. False Positives & False Negatives.mp4	14.3 MB
1. False Positives & False Negatives.srt	11.6 KB
2. Confusion Matrix.mp4	8.6 MB
2. Confusion Matrix.srt	7.7 KB
3. Accuracy Paradox.mp4	4.0 MB
3. Accuracy Paradox.srt	3.3 KB
4. CAP Curve.mp4	19.6 MB
4. CAP Curve.srt	16.6 KB
5. CAP Curve Analysis.mp4	12.1 MB
5. CAP Curve Analysis.srt	9.5 KB
6. Conclusion of Part 3 - Classification.html	3.6 KB
/2. -------------------- Part 1 Data Preprocessing --------------------/
1. Welcome to Part 1 - Data Preprocessing.mp4	3.1 MB
1. Welcome to Part 1 - Data Preprocessing.srt	2.6 KB
10. Feature Scaling.mp4	36.3 MB
10. Feature Scaling.srt	24.0 KB
11. And here is our Data Preprocessing Template!.mp4	20.6 MB
11. And here is our Data Preprocessing Template!.srt	14.5 KB
12. Data Preprocessing.html	0.1 KB
2. Get the dataset.mp4	22.2 MB
2. Get the dataset.srt	10.9 KB
3. Importing the Libraries.mp4	11.6 MB
3. Importing the Libraries.srt	8.3 KB
4. Importing the Dataset.mp4	24.5 MB
4. Importing the Dataset.srt	19.1 KB
5. For Python learners.html	1.8 KB
6. Missing Data.mp4	33.7 MB
6. Missing Data.srt	23.2 KB
6.1 missing_data.py.py	1.0 KB
7. Categorical Data.mp4	42.8 MB
7. Categorical Data.srt	27.7 KB
7.1 categorical_data.py.py	1.7 KB
8. WARNING - Update.html	2.8 KB
9. Splitting the Dataset into the Training set and Test set.mp4	40.9 MB
9. Splitting the Dataset into the Training set and Test set.srt	27.6 KB
/20. -------------------- Part 4 Clustering --------------------/
1. Welcome to Part 4 - Clustering.html	0.7 KB
/21. K-Means Clustering/
1. K-Means Clustering Intuition.mp4	28.2 MB
1. K-Means Clustering Intuition.srt	23.9 KB
2. K-Means Random Initialization Trap.mp4	16.1 MB
2. K-Means Random Initialization Trap.srt	13.3 KB
3. K-Means Selecting The Number Of Clusters.mp4	24.3 MB
3. K-Means Selecting The Number Of Clusters.srt	18.9 KB
4. How to get the dataset.mp4	12.3 MB
4. How to get the dataset.srt	4.9 KB
5. K-Means Clustering in Python.mp4	41.7 MB
5. K-Means Clustering in Python.srt	28.9 KB
6. K-Means Clustering in R.mp4	30.4 MB
6. K-Means Clustering in R.srt	19.9 KB
7. K-Means Clustering.html	0.1 KB
/22. Hierarchical Clustering/
1. Hierarchical Clustering Intuition.mp4	17.3 MB
1. Hierarchical Clustering Intuition.srt	14.9 KB
10. HC in R - Step 1.mp4	7.8 MB
10. HC in R - Step 1.srt	6.5 KB
11. HC in R - Step 2.mp4	11.7 MB
11. HC in R - Step 2.srt	8.3 KB
12. HC in R - Step 3.mp4	8.2 MB
12. HC in R - Step 3.srt	4.8 KB
13. HC in R - Step 4.mp4	7.8 MB
13. HC in R - Step 4.srt	3.9 KB
14. HC in R - Step 5.mp4	7.2 MB
14. HC in R - Step 5.srt	4.1 KB
15. Hierarchical Clustering.html	0.1 KB
16. Conclusion of Part 4 - Clustering.html	0.5 KB
16.1 Clustering-Pros-Cons.pdf.pdf	26.4 KB
2. Hierarchical Clustering How Dendrograms Work.mp4	18.3 MB
2. Hierarchical Clustering How Dendrograms Work.srt	14.7 KB
3. Hierarchical Clustering Using Dendrograms.mp4	23.9 MB
3. Hierarchical Clustering Using Dendrograms.srt	18.0 KB
4. How to get the dataset.mp4	12.3 MB
4. How to get the dataset.srt	4.9 KB
5. HC in Python - Step 1.mp4	11.2 MB
5. HC in Python - Step 1.srt	7.8 KB
6. HC in Python - Step 2.mp4	13.3 MB
6. HC in Python - Step 2.srt	9.7 KB
7. HC in Python - Step 3.mp4	12.9 MB
7. HC in Python - Step 3.srt	7.9 KB
8. HC in Python - Step 4.mp4	12.6 MB
8. HC in Python - Step 4.srt	6.6 KB
9. HC in Python - Step 5.mp4	8.8 MB
9. HC in Python - Step 5.srt	7.0 KB
/23. -------------------- Part 5 Association Rule Learning --------------------/
1. Welcome to Part 5 - Association Rule Learning.html	0.4 KB
/24. Apriori/
1. Apriori Intuition.mp4	36.7 MB
1. Apriori Intuition.srt	26.5 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Apriori in R - Step 1.mp4	45.0 MB
3. Apriori in R - Step 1.srt	31.8 KB
4. Apriori in R - Step 2.mp4	32.0 MB
4. Apriori in R - Step 2.srt	23.6 KB
5. Apriori in R - Step 3.mp4	46.0 MB
5. Apriori in R - Step 3.srt	31.9 KB
6. Apriori in Python - Step 1.mp4	39.8 MB
6. Apriori in Python - Step 1.srt	28.6 KB
7. Apriori in Python - Step 2.mp4	31.0 MB
7. Apriori in Python - Step 2.srt	23.1 KB
8. Apriori in Python - Step 3.mp4	28.3 MB
8. Apriori in Python - Step 3.srt	20.1 KB
/25. Eclat/
1. Eclat Intuition.mp4	11.2 MB
1. Eclat Intuition.srt	8.3 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Eclat in R.mp4	21.7 MB
3. Eclat in R.srt	16.2 KB
3.1 Eclat.zip.zip	49.7 KB
/26. -------------------- Part 6 Reinforcement Learning --------------------/
1. Welcome to Part 6 - Reinforcement Learning.html	1.2 KB
/27. Upper Confidence Bound (UCB)/
1. The Multi-Armed Bandit Problem.mp4	31.7 MB
1. The Multi-Armed Bandit Problem.srt	19.1 MB
10. Upper Confidence Bound in R - Step 3.mp4	49.5 MB
10. Upper Confidence Bound in R - Step 3.srt	25.9 KB
11. Upper Confidence Bound in R - Step 4.mp4	7.8 MB
11. Upper Confidence Bound in R - Step 4.srt	4.5 KB
2. Upper Confidence Bound (UCB) Intuition.mp4	30.7 MB
2. Upper Confidence Bound (UCB) Intuition.srt	22.4 KB
3. How to get the dataset.mp4	12.3 MB
3. How to get the dataset.srt	4.9 KB
4. Upper Confidence Bound in Python - Step 1.mp4	33.1 MB
4. Upper Confidence Bound in Python - Step 1.srt	22.4 KB
5. Upper Confidence Bound in Python - Step 2.mp4	37.2 MB
5. Upper Confidence Bound in Python - Step 2.srt	25.9 KB
6. Upper Confidence Bound in Python - Step 3.mp4	43.1 MB
6. Upper Confidence Bound in Python - Step 3.srt	27.6 KB
7. Upper Confidence Bound in Python - Step 4.mp4	9.6 MB
7. Upper Confidence Bound in Python - Step 4.srt	5.1 KB
8. Upper Confidence Bound in R - Step 1.mp4	29.4 MB
8. Upper Confidence Bound in R - Step 1.srt	21.0 KB
9. Upper Confidence Bound in R - Step 2.mp4	30.4 MB
9. Upper Confidence Bound in R - Step 2.srt	22.7 KB
/28. Thompson Sampling/
1. Thompson Sampling Intuition.mp4	39.1 MB
1. Thompson Sampling Intuition.srt	28.2 KB
2. Algorithm Comparison UCB vs Thompson Sampling.mp4	14.8 MB
2. Algorithm Comparison UCB vs Thompson Sampling.srt	11.4 KB
3. How to get the dataset.mp4	12.3 MB
3. How to get the dataset.srt	4.9 KB
4. Thompson Sampling in Python - Step 1.mp4	45.2 MB
4. Thompson Sampling in Python - Step 1.srt	29.6 KB
5. Thompson Sampling in Python - Step 2.mp4	8.8 MB
5. Thompson Sampling in Python - Step 2.srt	5.9 KB
6. Thompson Sampling in R - Step 1.mp4	42.9 MB
6. Thompson Sampling in R - Step 1.srt	28.5 KB
7. Thompson Sampling in R - Step 2.mp4	7.8 MB
7. Thompson Sampling in R - Step 2.srt	5.4 KB
/29. -------------------- Part 7 Natural Language Processing --------------------/
1. Welcome to Part 7 - Natural Language Processing.html	1.7 KB
10. Natural Language Processing in Python - Step 7.mp4	17.9 MB
10. Natural Language Processing in Python - Step 7.srt	10.0 KB
11. Natural Language Processing in Python - Step 8.mp4	41.4 MB
11. Natural Language Processing in Python - Step 8.srt	24.4 KB
12. Natural Language Processing in Python - Step 9.mp4	14.7 MB
12. Natural Language Processing in Python - Step 9.srt	8.4 KB
13. Natural Language Processing in Python - Step 10.mp4	25.3 MB
13. Natural Language Processing in Python - Step 10.srt	14.7 KB
14. Homework Challenge.html	1.4 KB
15. Natural Language Processing in R - Step 1.mp4	42.3 MB
15. Natural Language Processing in R - Step 1.srt	24.6 KB
16. Natural Language Processing in R - Step 2.mp4	18.3 MB
16. Natural Language Processing in R - Step 2.srt	13.2 KB
17. Natural Language Processing in R - Step 3.mp4	14.2 MB
17. Natural Language Processing in R - Step 3.srt	10.4 KB
18. Natural Language Processing in R - Step 4.mp4	6.8 MB
18. Natural Language Processing in R - Step 4.srt	4.8 KB
19. Natural Language Processing in R - Step 5.mp4	4.8 MB
19. Natural Language Processing in R - Step 5.srt	3.3 KB
2. Natural Language Processing Intuition.mp4	31.1 MB
2. Natural Language Processing Intuition.srt	7.2 KB
20. Natural Language Processing in R - Step 6.mp4	13.3 MB
20. Natural Language Processing in R - Step 6.srt	8.6 KB
21. Natural Language Processing in R - Step 7.mp4	7.9 MB
21. Natural Language Processing in R - Step 7.srt	5.7 KB
22. Natural Language Processing in R - Step 8.mp4	13.9 MB
22. Natural Language Processing in R - Step 8.srt	8.2 KB
23. Natural Language Processing in R - Step 9.mp4	30.4 MB
23. Natural Language Processing in R - Step 9.srt	20.1 KB
24. Natural Language Processing in R - Step 10.mp4	43.2 MB
24. Natural Language Processing in R - Step 10.srt	26.9 KB
25. Homework Challenge.html	1.4 KB
3. How to get the dataset.mp4	12.3 MB
3. How to get the dataset.srt	4.9 KB
4. Natural Language Processing in Python - Step 1.mp4	36.9 MB
4. Natural Language Processing in Python - Step 1.srt	18.8 KB
5. Natural Language Processing in Python - Step 2.mp4	23.0 MB
5. Natural Language Processing in Python - Step 2.srt	16.2 KB
6. Natural Language Processing in Python - Step 3.mp4	3.6 MB
6. Natural Language Processing in Python - Step 3.srt	2.7 KB
7. Natural Language Processing in Python - Step 4.mp4	25.2 MB
7. Natural Language Processing in Python - Step 4.srt	17.9 KB
8. Natural Language Processing in Python - Step 5.mp4	15.6 MB
8. Natural Language Processing in Python - Step 5.srt	10.9 KB
9. Natural Language Processing in Python - Step 6.mp4	6.8 MB
9. Natural Language Processing in Python - Step 6.srt	4.5 KB
/3. -------------------- Part 2 Regression --------------------/
1. Welcome to Part 2 - Regression.html	0.9 KB
/30. -------------------- Part 8 Deep Learning --------------------/
1. Welcome to Part 8 - Deep Learning.html	0.9 KB
2. What is Deep Learning.mp4	32.8 MB
2. What is Deep Learning.srt	18.6 KB
/31. Artificial Neural Networks/
1. Plan of attack.mp4	5.0 MB
1. Plan of attack.srt	4.1 KB
10. Business Problem Description.mp4	17.2 MB
10. Business Problem Description.srt	7.5 KB
11. Installing Keras.html	1.4 KB
12. ANN in Python - Step 1.mp4	30.7 MB
12. ANN in Python - Step 1.srt	20.5 KB
13. ANN in Python - Step 2.mp4	50.4 MB
13. ANN in Python - Step 2.srt	29.6 KB
14. ANN in Python - Step 3.mp4	8.8 MB
14. ANN in Python - Step 3.srt	5.3 KB
15. ANN in Python - Step 4.mp4	6.2 MB
15. ANN in Python - Step 4.srt	4.0 KB
16. ANN in Python - Step 5.mp4	31.0 MB
16. ANN in Python - Step 5.srt	20.0 KB
17. ANN in Python - Step 6.mp4	7.4 MB
17. ANN in Python - Step 6.srt	4.6 KB
18. ANN in Python - Step 7.mp4	9.4 MB
18. ANN in Python - Step 7.srt	5.8 KB
19. ANN in Python - Step 8.mp4	19.0 MB
19. ANN in Python - Step 8.srt	11.3 KB
2. The Neuron.mp4	31.3 MB
2. The Neuron.srt	25.6 KB
20. ANN in Python - Step 9.mp4	17.7 MB
20. ANN in Python - Step 9.srt	9.7 KB
21. ANN in Python - Step 10.mp4	17.9 MB
21. ANN in Python - Step 10.srt	10.6 KB
22. ANN in R - Step 1.mp4	40.4 MB
22. ANN in R - Step 1.srt	27.4 KB
23. ANN in R - Step 2.mp4	14.9 MB
23. ANN in R - Step 2.srt	10.4 KB
24. ANN in R - Step 3.mp4	30.3 MB
24. ANN in R - Step 3.srt	19.3 KB
25. ANN in R - Step 4 (Last step).mp4	35.1 MB
25. ANN in R - Step 4 (Last step).srt	21.2 KB
3. The Activation Function.mp4	15.5 MB
3. The Activation Function.srt	12.3 KB
4. How do Neural Networks work.mp4	24.7 MB
4. How do Neural Networks work.srt	19.6 KB
5. How do Neural Networks learn.mp4	27.8 MB
5. How do Neural Networks learn.srt	19.4 KB
6. Gradient Descent.mp4	19.4 MB
6. Gradient Descent.srt	14.4 KB
7. Stochastic Gradient Descent.mp4	17.6 MB
7. Stochastic Gradient Descent.srt	12.4 KB
8. Backpropagation.mp4	11.5 MB
8. Backpropagation.srt	7.3 KB
9. How to get the dataset.mp4	12.3 MB
9. How to get the dataset.srt	4.9 KB
/32. Convolutional Neural Networks/
1. Plan of attack.mp4	6.2 MB
1. Plan of attack.srt	5.4 KB
10. How to get the dataset.mp4	12.3 MB
10. How to get the dataset.srt	4.9 KB
11. Installing Keras.html	0.9 KB
12. CNN in Python - Step 1.mp4	26.1 MB
12. CNN in Python - Step 1.srt	18.8 KB
13. CNN in Python - Step 2.mp4	6.1 MB
13. CNN in Python - Step 2.srt	4.6 KB
14. CNN in Python - Step 3.mp4	2.3 MB
14. CNN in Python - Step 3.srt	1.8 KB
15. CNN in Python - Step 4.mp4	28.5 MB
15. CNN in Python - Step 4.srt	19.7 KB
16. CNN in Python - Step 5.mp4	10.4 MB
16. CNN in Python - Step 5.srt	7.7 KB
17. CNN in Python - Step 6.mp4	10.2 MB
17. CNN in Python - Step 6.srt	7.8 KB
18. CNN in Python - Step 7.mp4	13.6 MB
18. CNN in Python - Step 7.srt	9.3 KB
19. CNN in Python - Step 8.mp4	7.1 MB
19. CNN in Python - Step 8.srt	4.7 KB
2. What are convolutional neural networks.mp4	30.9 MB
2. What are convolutional neural networks.srt	22.6 KB
20. CNN in Python - Step 9.mp4	49.1 MB
20. CNN in Python - Step 9.srt	30.1 KB
21. CNN in Python - Step 10.mp4	21.6 MB
21. CNN in Python - Step 10.srt	13.3 KB
22. CNN in R.html	2.4 KB
3. Step 1 - Convolution Operation.mp4	32.5 MB
3. Step 1 - Convolution Operation.srt	23.8 KB
4. Step 1(b) - ReLU Layer.mp4	14.8 MB
4. Step 1(b) - ReLU Layer.srt	9.4 KB
5. Step 2 - Pooling.mp4	42.2 MB
5. Step 2 - Pooling.srt	21.5 KB
6. Step 3 - Flattening.mp4	3.4 MB
6. Step 3 - Flattening.srt	2.6 KB
7. Step 4 - Full Connection.mp4	44.8 MB
7. Step 4 - Full Connection.srt	29.3 KB
8. Summary.mp4	8.3 MB
8. Summary.srt	6.2 KB
9. Softmax & Cross-Entropy.mp4	34.8 MB
9. Softmax & Cross-Entropy.srt	25.9 KB
/33. -------------------- Part 9 Dimensionality Reduction --------------------/
1. Welcome to Part 9 - Dimensionality Reduction.html	1.3 KB
/34. Principal Component Analysis (PCA)/
1. Principal Component Analysis (PCA) Intuition.mp4	33.7 MB
1. Principal Component Analysis (PCA) Intuition.srt	5.2 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. PCA in Python - Step 1.mp4	33.5 MB
3. PCA in Python - Step 1.srt	18.1 KB
4. PCA in Python - Step 2.mp4	23.1 MB
4. PCA in Python - Step 2.srt	12.1 KB
5. PCA in Python - Step 3.mp4	26.7 MB
5. PCA in Python - Step 3.srt	15.2 KB
6. PCA in R - Step 1.mp4	32.1 MB
6. PCA in R - Step 1.srt	19.1 KB
7. PCA in R - Step 2.mp4	30.4 MB
7. PCA in R - Step 2.srt	17.3 KB
8. PCA in R - Step 3.mp4	38.5 MB
8. PCA in R - Step 3.srt	20.2 KB
/35. Linear Discriminant Analysis (LDA)/
1. Linear Discriminant Analysis (LDA) Intuition.mp4	28.3 MB
1. Linear Discriminant Analysis (LDA) Intuition.srt	5.2 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. LDA in Python.mp4	47.6 MB
3. LDA in Python.srt	27.1 KB
4. LDA in R.mp4	53.8 MB
4. LDA in R.srt	30.4 KB
/36. Kernel PCA/
1. How to get the dataset.mp4	12.3 MB
1. How to get the dataset.srt	4.9 KB
2. Kernel PCA in Python.mp4	35.0 MB
2. Kernel PCA in Python.srt	22.0 KB
3. Kernel PCA in R.mp4	59.3 MB
3. Kernel PCA in R.srt	31.5 KB
/37. -------------------- Part 10 Model Selection & Boosting --------------------/
1. Welcome to Part 10 - Model Selection & Boosting.html	0.9 KB
/38. Model Selection/
1. How to get the dataset.mp4	12.3 MB
1. How to get the dataset.srt	4.9 KB
2. k-Fold Cross Validation in Python.mp4	34.4 MB
2. k-Fold Cross Validation in Python.srt	20.7 KB
3. k-Fold Cross Validation in R.mp4	45.8 MB
3. k-Fold Cross Validation in R.srt	28.6 KB
4. Grid Search in Python - Step 1.mp4	40.1 MB
4. Grid Search in Python - Step 1.srt	22.6 KB
5. Grid Search in Python - Step 2.mp4	30.9 MB
5. Grid Search in Python - Step 2.srt	15.7 KB
6. Grid Search in R.mp4	37.3 MB
6. Grid Search in R.srt	21.4 KB
/39. XGBoost/
1. How to get the dataset.mp4	12.3 MB
1. How to get the dataset.srt	12.3 MB
2. XGBoost in Python - Step 1.mp4	22.4 MB
2. XGBoost in Python - Step 1.srt	14.0 KB
3. XGBoost in Python - Step 2.mp4	33.5 MB
3. XGBoost in Python - Step 2.srt	19.3 KB
4. XGBoost in R.mp4	49.6 MB
4. XGBoost in R.srt	26.6 KB
5. THANK YOU bonus video.mp4	54.8 MB
5. THANK YOU bonus video.srt	2.4 KB
/4. Simple Linear Regression/
1. How to get the dataset.mp4	12.3 MB
1. How to get the dataset.srt	4.9 KB
10. Simple Linear Regression in R - Step 2.mp4	15.0 MB
10. Simple Linear Regression in R - Step 2.srt	9.1 KB
11. Simple Linear Regression in R - Step 3.mp4	9.1 MB
11. Simple Linear Regression in R - Step 3.srt	5.6 KB
12. Simple Linear Regression in R - Step 4.mp4	39.2 MB
12. Simple Linear Regression in R - Step 4.srt	24.5 KB
13. Simple Linear Regression.html	0.1 KB
2. Dataset + Business Problem Description.mp4	7.0 MB
2. Dataset + Business Problem Description.srt	4.2 KB
3. Simple Linear Regression Intuition - Step 1.mp4	9.9 MB
3. Simple Linear Regression Intuition - Step 1.srt	8.5 KB
4. Simple Linear Regression Intuition - Step 2.mp4	5.6 MB
4. Simple Linear Regression Intuition - Step 2.srt	4.4 KB
5. Simple Linear Regression in Python - Step 1.mp4	22.8 MB
5. Simple Linear Regression in Python - Step 1.srt	15.8 KB
6. Simple Linear Regression in Python - Step 2.mp4	19.7 MB
6. Simple Linear Regression in Python - Step 2.srt	12.6 KB
7. Simple Linear Regression in Python - Step 3.mp4	16.4 MB
7. Simple Linear Regression in Python - Step 3.srt	10.1 KB
8. Simple Linear Regression in Python - Step 4.mp4	32.3 MB
8. Simple Linear Regression in Python - Step 4.srt	23.0 KB
9. Simple Linear Regression in R - Step 1.mp4	10.0 MB
9. Simple Linear Regression in R - Step 1.srt	7.9 KB
/40. Bonus Lectures/
1. YOUR SPECIAL BONUS.html	4.8 KB
/5. Multiple Linear Regression/
1. How to get the dataset.mp4	12.3 MB
1. How to get the dataset.srt	4.9 KB
10. Multiple Linear Regression in Python - Step 2.mp4	7.6 MB
10. Multiple Linear Regression in Python - Step 2.srt	4.2 KB
11. Multiple Linear Regression in Python - Step 3.mp4	15.0 MB
11. Multiple Linear Regression in Python - Step 3.srt	8.5 KB
12. Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4	25.0 MB
12. Multiple Linear Regression in Python - Backward Elimination - Preparation.srt	15.3 KB
13. Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.mp4	34.2 MB
13. Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.srt	20.2 KB
14. Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4	28.5 MB
14. Multiple Linear Regression in Python - Backward Elimination - Homework Solution.srt	14.5 KB
15. Multiple Linear Regression in Python - Automatic Backward Elimination.html	2.2 KB
16. Multiple Linear Regression in R - Step 1.mp4	18.8 MB
16. Multiple Linear Regression in R - Step 1.srt	12.1 KB
17. Multiple Linear Regression in R - Step 2.mp4	27.2 MB
17. Multiple Linear Regression in R - Step 2.srt	15.8 KB
18. Multiple Linear Regression in R - Step 3.mp4	10.9 MB
18. Multiple Linear Regression in R - Step 3.srt	7.2 KB
19. Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.mp4	41.7 MB
19. Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.srt	28.1 KB
2. Dataset + Business Problem Description.mp4	10.5 MB
2. Dataset + Business Problem Description.srt	5.8 KB
20. Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4	18.1 MB
20. Multiple Linear Regression in R - Backward Elimination - Homework Solution.srt	12.1 KB
21. Multiple Linear Regression in R - Automatic Backward Elimination.html	0.7 KB
22. Multiple Linear Regression.html	0.1 KB
3. Multiple Linear Regression Intuition - Step 1.mp4	1.9 MB
3. Multiple Linear Regression Intuition - Step 1.srt	1.6 KB
4. Multiple Linear Regression Intuition - Step 2.mp4	1.9 MB
4. Multiple Linear Regression Intuition - Step 2.srt	1.5 KB
5. Multiple Linear Regression Intuition - Step 3.mp4	15.0 MB
5. Multiple Linear Regression Intuition - Step 3.srt	11.0 KB
6. Multiple Linear Regression Intuition - Step 4.mp4	4.7 MB
6. Multiple Linear Regression Intuition - Step 4.srt	3.6 KB
7. Prerequisites What is the P-Value.html	0.7 KB
8. Multiple Linear Regression Intuition - Step 5.mp4	30.2 MB
8. Multiple Linear Regression Intuition - Step 5.srt	24.1 KB
9. Multiple Linear Regression in Python - Step 1.mp4	41.5 MB
9. Multiple Linear Regression in Python - Step 1.srt	25.0 KB
/6. Polynomial Regression/
1. Polynomial Regression Intuition.mp4	9.9 MB
1. Polynomial Regression Intuition.srt	8.0 KB
10. Polynomial Regression in R - Step 3.mp4	45.4 MB
10. Polynomial Regression in R - Step 3.srt	31.6 KB
11. Polynomial Regression in R - Step 4.mp4	23.4 MB
11. Polynomial Regression in R - Step 4.srt	15.8 KB
12. R Regression Template.mp4	26.6 MB
12. R Regression Template.srt	19.1 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Polynomial Regression in Python - Step 1.mp4	26.1 MB
3. Polynomial Regression in Python - Step 1.srt	17.9 KB
4. Polynomial Regression in Python - Step 2.mp4	28.4 MB
4. Polynomial Regression in Python - Step 2.srt	17.6 KB
5. Polynomial Regression in Python - Step 3.mp4	45.1 MB
5. Polynomial Regression in Python - Step 3.srt	32.2 KB
6. Polynomial Regression in Python - Step 4.mp4	14.2 MB
6. Polynomial Regression in Python - Step 4.srt	8.9 KB
7. Python Regression Template.mp4	28.8 MB
7. Python Regression Template.srt	16.8 KB
8. Polynomial Regression in R - Step 1.mp4	18.7 MB
8. Polynomial Regression in R - Step 1.srt	14.5 KB
9. Polynomial Regression in R - Step 2.mp4	25.0 MB
9. Polynomial Regression in R - Step 2.srt	15.6 KB
/7. Support Vector Regression (SVR)/
1. How to get the dataset.mp4	12.3 MB
1. How to get the dataset.srt	4.9 KB
2. SVR Intuition.mp4	48.9 MB
2. SVR Intuition.srt	11.6 KB
3. SVR in Python.mp4	48.4 MB
3. SVR in Python.srt	31.6 KB
4. SVR in R.mp4	27.1 MB
4. SVR in R.srt	27.2 MB
/8. Decision Tree Regression/
1. Decision Tree Regression Intuition.mp4	23.8 MB
1. Decision Tree Regression Intuition.srt	17.5 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Decision Tree Regression in Python.mp4	35.2 MB
3. Decision Tree Regression in Python.srt	24.3 KB
4. Decision Tree Regression in R.mp4	46.5 MB
4. Decision Tree Regression in R.srt	32.9 KB
/9. Random Forest Regression/
1. Random Forest Regression Intuition.mp4	14.5 MB
1. Random Forest Regression Intuition.srt	10.5 KB
2. How to get the dataset.mp4	12.3 MB
2. How to get the dataset.srt	4.9 KB
3. Random Forest Regression in Python.mp4	41.4 MB
3. Random Forest Regression in Python.srt	28.2 KB
4. Random Forest Regression in R.mp4	42.3 MB
4. Random Forest Regression in R.srt	28.8 KB
/
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
[FreeCourseWorld.Com].url	0.1 KB
Total files 575