DevCourseWeb com Udemy Python for Machine Learning The Complete Beginner Course

DevCourseWeb com Udemy Python for Machine Learning The Complete Beginner Course

Name	[ DevCourseWeb.com ] Udemy - Python for Machine Learning - The Complete Beginner's Course	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	718.6 MB
Total Files	177
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Hash	DDCAC72F14747E53ED1389E76468DCBDAE1E3822

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Get Bonus Downloads Here.url	0.2 KB
/.../1. Introduction to Machine Learning/
1. What is Machine Learning.mp4	7.8 MB
1. What is Machine Learning.srt	2.1 KB
2. Applications of Machine Learning.mp4	6.8 MB
2. Applications of Machine Learning.srt	2.0 KB
3. Machine learning Methods.mp4	3.9 MB
3. Machine learning Methods.srt	0.4 KB
4. What is Supervised learning.mp4	6.5 MB
4. What is Supervised learning.srt	1.3 KB
5. What is Unsupervised learning.mp4	6.2 MB
5. What is Unsupervised learning.srt	1.0 KB
6. Supervised learning vs Unsupervised learning.mp4	15.0 MB
6. Supervised learning vs Unsupervised learning.srt	4.6 KB
7. Course Materials.html	0.1 KB
7.1 50_Startups.csv	2.4 KB
7.10 Movie_Id_Titles.original	51.0 KB
7.11 MultipleLinearRegression.ipynb	8.7 KB
7.12 Recommender Systems with Python.ipynb	125.3 KB
7.13 salaries.csv	0.7 KB
7.14 u.data	2.1 MB
7.15 user data.csv	10.9 KB
7.2 Decision_tree.ipynb	14.7 KB
7.3 homeprices.csv	0.1 KB
7.4 K-means algorithm numpy&pandas clustering.ipynb	104.8 KB
7.5 KNN_Binary_Classification.ipynb	25.8 KB
7.6 linear_regression_houseprice.ipynb	16.7 KB
7.7 logistic_regression_Binary_Classification.ipynb	2.8 KB
7.8 mall customers data.csv	4.4 KB
7.9 mallCustomerData.txt	4.0 KB
/.../2. Simple Linear Regression/
1. Introduction to regression.mp4	9.4 MB
1. Introduction to regression.srt	1.9 KB
2. How Does Linear Regression Work.mp4	8.1 MB
2. How Does Linear Regression Work.srt	1.9 KB
3. Line representation.mp4	5.7 MB
3. Line representation.srt	0.8 KB
4. Implementation in python Importing libraries & datasets.mp4	7.9 MB
4. Implementation in python Importing libraries & datasets.srt	1.5 KB
5. Implementation in python Distribution of the data.mp4	9.9 MB
5. Implementation in python Distribution of the data.srt	2.2 KB
6. Implementation in python Creating a linear regression object.mp4	13.9 MB
6. Implementation in python Creating a linear regression object.srt	2.9 KB
/.../3. Multiple Linear Regression/
1. Understanding Multiple linear regression.mp4	6.6 MB
1. Understanding Multiple linear regression.srt	1.5 KB
2. Implementation in python Exploring the dataset.mp4	14.0 MB
2. Implementation in python Exploring the dataset.srt	3.6 KB
3. Implementation in python Encoding Categorical Data.mp4	30.3 MB
3. Implementation in python Encoding Categorical Data.srt	5.8 KB
4. Implementation in python Splitting data into Train and Test Sets.mp4	9.3 MB
4. Implementation in python Splitting data into Train and Test Sets.srt	1.6 KB
5. Implementation in python Training the model on the Training set.mp4	9.0 MB
5. Implementation in python Training the model on the Training set.srt	1.0 KB
6. Implementation in python Predicting the Test Set results.mp4	18.7 MB
6. Implementation in python Predicting the Test Set results.srt	2.9 KB
7. Evaluating the performance of the regression model.mp4	6.3 MB
7. Evaluating the performance of the regression model.srt	1.3 KB
8. Root Mean Squared Error in Python.mp4	12.4 MB
8. Root Mean Squared Error in Python.srt	2.3 KB
/.../4. Classification Algorithms K-Nearest Neighbors/
1. Introduction to classification.mp4	4.9 MB
1. Introduction to classification.srt	1.2 KB
10. Implementation in python Results prediction & Confusion matrix.mp4	10.1 MB
10. Implementation in python Results prediction & Confusion matrix.srt	1.4 KB
2. K-Nearest Neighbors algorithm.mp4	6.3 MB
2. K-Nearest Neighbors algorithm.srt	0.9 KB
3. Example of KNN.mp4	3.7 MB
3. Example of KNN.srt	0.4 KB
4. K-Nearest Neighbours (KNN) using python.mp4	6.4 MB
4. K-Nearest Neighbours (KNN) using python.srt	1.2 KB
5. Implementation in python Importing required libraries.mp4	5.4 MB
5. Implementation in python Importing required libraries.srt	0.4 KB
6. Implementation in python Importing the dataset.mp4	9.7 MB
6. Implementation in python Importing the dataset.srt	1.3 KB
7. Implementation in python Splitting data into Train and Test Sets.mp4	20.6 MB
7. Implementation in python Splitting data into Train and Test Sets.srt	2.9 KB
8. Implementation in python Feature Scaling.mp4	6.0 MB
8. Implementation in python Feature Scaling.srt	0.3 KB
9. Implementation in python Importing the KNN classifier.mp4	13.1 MB
9. Implementation in python Importing the KNN classifier.srt	2.0 KB
/.../5. Classification Algorithms Decision Tree/
1. Introduction to decision trees.mp4	6.8 MB
1. Introduction to decision trees.srt	1.5 KB
2. What is Entropy.mp4	5.5 MB
2. What is Entropy.srt	1.5 KB
3. Exploring the dataset.mp4	6.2 MB
3. Exploring the dataset.srt	1.4 KB
4. Decision tree structure.mp4	6.7 MB
4. Decision tree structure.srt	1.4 KB
5. Implementation in python Importing libraries & datasets.mp4	4.9 MB
5. Implementation in python Importing libraries & datasets.srt	0.9 KB
6. Implementation in python Encoding Categorical Data.mp4	17.8 MB
6. Implementation in python Encoding Categorical Data.srt	3.5 KB
7. Implementation in python Splitting data into Train and Test Sets.mp4	5.2 MB
7. Implementation in python Splitting data into Train and Test Sets.srt	0.9 KB
8. Implementation in python Results prediction & Accuracy.mp4	10.9 MB
8. Implementation in python Results prediction & Accuracy.srt	2.7 KB
/.../6. Classification Algorithms Logistic regression/
1. Introduction.mp4	6.9 MB
1. Introduction.srt	1.5 KB
2. Implementation steps.mp4	5.8 MB
2. Implementation steps.srt	1.0 KB
3. Implementation in python Importing libraries & datasets.mp4	7.2 MB
3. Implementation in python Importing libraries & datasets.srt	1.9 KB
4. Implementation in python Splitting data into Train and Test Sets.mp4	7.5 MB
4. Implementation in python Splitting data into Train and Test Sets.srt	1.6 KB
5. Implementation in python Pre-processing.mp4	13.8 MB
5. Implementation in python Pre-processing.srt	1.9 KB
6. Implementation in python Training the model.mp4	8.2 MB
6. Implementation in python Training the model.srt	1.2 KB
7. Implementation in python Results prediction & Confusion matrix.mp4	14.1 MB
7. Implementation in python Results prediction & Confusion matrix.srt	2.6 KB
8. Logistic Regression vs Linear Regression.mp4	11.3 MB
8. Logistic Regression vs Linear Regression.srt	2.9 KB
/7. Clustering/
1. Introduction to clustering.mp4	4.5 MB
1. Introduction to clustering.srt	0.8 KB
10. Importing the dataset.mp4	13.4 MB
10. Importing the dataset.srt	3.3 KB
11. Visualizing the dataset.mp4	13.0 MB
11. Visualizing the dataset.srt	2.9 KB
12. Defining the classifier.mp4	8.0 MB
12. Defining the classifier.srt	1.7 KB
13. 3D Visualization of the clusters.mp4	8.2 MB
13. 3D Visualization of the clusters.srt	1.6 KB
14. 3D Visualization of the predicted values.mp4	13.5 MB
14. 3D Visualization of the predicted values.srt	2.8 KB
15. Number of predicted clusters.mp4	9.9 MB
15. Number of predicted clusters.srt	2.1 KB
2. Use cases.mp4	4.2 MB
2. Use cases.srt	1.0 KB
3. K-Means Clustering Algorithm.mp4	6.9 MB
3. K-Means Clustering Algorithm.srt	1.6 KB
4. Elbow method.mp4	7.4 MB
4. Elbow method.srt	1.8 KB
5. Steps of the Elbow method.mp4	6.1 MB
5. Steps of the Elbow method.srt	1.1 KB
6. Implementation in python.mp4	19.9 MB
6. Implementation in python.srt	3.7 KB
7. Hierarchical clustering.mp4	7.8 MB
7. Hierarchical clustering.srt	1.3 KB
8. Density-based clustering.mp4	8.2 MB
8. Density-based clustering.srt	1.8 KB
9. Implementation of k-means clustering in python.mp4	4.1 MB
9. Implementation of k-means clustering in python.srt	0.8 KB
/8. Recommender System/
1. Introduction.mp4	7.9 MB
1. Introduction.srt	1.6 KB
10. Data pre-processing.mp4	11.3 MB
10. Data pre-processing.srt	2.2 KB
11. Sorting the most-rated movies.mp4	9.3 MB
11. Sorting the most-rated movies.srt	0.9 KB
12. Grabbing the ratings for two movies.mp4	5.7 MB
12. Grabbing the ratings for two movies.srt	1.5 KB
13. Correlation between the most-rated movies.mp4	13.9 MB
13. Correlation between the most-rated movies.srt	2.1 KB
14. Sorting the data by correlation.mp4	6.4 MB
14. Sorting the data by correlation.srt	1.5 KB
15. Filtering out movies.mp4	5.0 MB
15. Filtering out movies.srt	0.7 KB
16. Sorting values.mp4	7.2 MB
16. Sorting values.srt	1.1 KB
17. Repeating the process for another movie.mp4	13.3 MB
17. Repeating the process for another movie.srt	2.6 KB
18. Quiz Time.html	0.2 KB
2. Collaborative Filtering in Recommender Systems.mp4	4.4 MB
2. Collaborative Filtering in Recommender Systems.srt	0.7 KB
3. Content-based Recommender System.mp4	5.1 MB
3. Content-based Recommender System.srt	0.8 KB
4. Implementation in python Importing libraries & datasets.mp4	10.8 MB
4. Implementation in python Importing libraries & datasets.srt	3.2 KB
5. Merging datasets into one dataframe.mp4	4.4 MB
5. Merging datasets into one dataframe.srt	0.6 KB
6. Sorting by title and rating.mp4	20.3 MB
6. Sorting by title and rating.srt	5.8 KB
7. Histogram showing number of ratings.mp4	5.9 MB
7. Histogram showing number of ratings.srt	0.8 KB
8. Frequency distribution.mp4	6.3 MB
8. Frequency distribution.srt	1.3 KB
9. Jointplot of the ratings and number of ratings.mp4	7.6 MB
9. Jointplot of the ratings and number of ratings.srt	1.4 KB
/9. Conclusion/
1. Conclusion.mp4	2.9 MB
1. Conclusion.srt	0.4 KB
~Get Your Files Here !/
Bonus Resources.txt	0.4 KB
Total files 177