| 001 Data Preprocessing.mp4 | 104 MB | ||
| 001 Data.csv | 204.8 B | ||
| 001 DataPreprocessing.py | 1.2 KB | ||
| 001 K-Means Clustering.mp4 | 101 MB | ||
| 001 K-Nearest Neighbour.mp4 | 47.2 MB | ||
| 001 Simple Linear Regression.mp4 | 100.9 MB | ||
| 002 Hierarchical Clustering.mp4 | 98 MB | ||
| 002 Multiple Linear Regression.mp4 | 293.4 MB | ||
| 002 Social_Network_Ads.csv | 10.7 KB | ||
| 002 Support Vector Machine (SVM).mp4 | 101.7 MB | ||
| 002 knn.py | 1 KB | ||
| 003 Kernel SVM.mp4 | 33.9 MB | ||
| 003 Polynomial Linear Regression.mp4 | 99.3 MB | ||
| 003 Social_Network_Ads.csv | 10.7 KB | ||
| 003 svm.py | 921.6 B | ||
| 004 Decision Tree Classification.mp4 | 19.4 MB | ||
| 004 Social_Network_Ads.csv | 10.7 KB | ||
| 004 Support Vector Regression(SVR).mp4 | 155.1 MB | ||
| 004 kernel_svm.py | 921.6 B | ||
| 005 Decision Tree Regression.mp4 | 53.5 MB | ||
| 005 Random Forest Classification.mp4 | 20.4 MB | ||
| 005 Social_Network_Ads.csv | 10.7 KB | ||
| 005 decision_tree_classification.py | 1 KB | ||
| 006 Random Forest Regression.mp4 | 25 MB | ||
| 006 Social_Network_Ads.csv | 10.7 KB | ||
| 006 random_forest_classification.py | 1 KB | ||
| 007 Logistic Regression.mp4 | 106.9 MB | ||
| 007 Salary_Data.csv | 409.6 B | ||
| 007 simple_linear_regression.py | 1.4 KB | ||
| 008 50_Startups.csv | 2.4 KB | ||
| 008 Multi_Linear_Regression.py | 1.9 KB | ||
| 009 Polynomial_linear_regression.py | 1.5 KB | ||
| 009 Position_Salaries.csv | 204.8 B | ||
| 010 Position_Salaries.csv | 204.8 B | ||
| 010 support_vector_regression.py | 1.4 KB | ||
| 011 Position_Salaries.csv | 204.8 B | ||
| 011 decision_tree_regression.py | 921.6 B | ||
| 012 Position_Salaries.csv | 204.8 B | ||
| 012 random_forest_regression.py | 921.6 B | ||
| 013 Log_regression.py | 1 KB | ||
| 013 Social_Network_Ads.csv | 10.7 KB | ||
| 014 Mall_Customers.csv | 4.2 KB | ||
| 014 kmeans.py | 1.5 KB | ||
| 015 Mall_Customers.csv | 4.2 KB | ||
| 015 hc.py | 716.8 B | ||
| Downloaded from 1337x.html | 512 B | ||
| ▲ 46 total files | |||
Knowledge should not be limited to those who can afford it or those willing to pay for it.
If you found this course useful and are financially stable please consider supporting the creators by buying the course :)
Machine Learning From Basic to Advanced
Learn to create Machine Learning Algorithms in Python Data Science enthusiasts. Code templates included.
What you'll learn
* Master Machine Learning on Python
* Make accurate predictions
* Make robust Machine Learning models
* Use Machine Learning for personal purpose
* Have a great intuition of many Machine Learning models
* Know which Machine Learning model to choose for each type of problem
* Use SciKit-Learn for Machine Learning Tasks
* Make predictions using linear regression, polynomial regression, and multiple regression
* Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, etc.
Interested in the field of Machine Learning? Then this course is for you!
This course has been designed by Code Warriors the ML Enthusiasts so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.
We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:
Part 1 - Data Preprocessing
Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression.
Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 - Clustering: K-Means, Hierarchical Clustering.
And as a bonus, this course includes Python code templates which you can download and use on your own projects.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 779 MB | freecoursewb | 3 weeks | 24 | 1 | |
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Udemy - Spark Machine Learning Project (House Sale Price Prediction) Posted by
freecoursewb in Other
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1.7 GB | freecoursewb | 1 month | 9 | 4 |
| 3.4 GB | freecoursewb | 2 months | 19 | 5 | |
| 1.2 GB | freecoursewb | 2 months | 12 | 3 | |
| 1.9 GB | freecoursewb | 3 months | 4 | 0 |
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