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

what are you learning

  • Mastering Machine Learning in Python and AR
  • Learn how unique the many machine learning modules are.
  • Make accurate predictions.
  • Build powerful analytics
  • Building powerful models for machine learning
  • Create strong added value for your business.
  • Use machine learning for personal purposes.
  • Perform specific topics such as reinforcement learning, NLP and deep learning.
  • Control the latest technology such as directional reduction.
  • Find out which machine learning model to choose for each type of problem.
  • Build an army of powerful machine learning units and learn how to combine them to solve any problem.


Some high school math levels.

He explained

Are you interested in machine learning? So this course is for you!

This course is created by two professional data scientists so that we can share our knowledge and help you easily learn complex theories, algorithms and coding libraries.

We will guide you step by step into the world of machine - learning. With each lesson, you will develop new skills and improve your understanding of this profitable and challenging subdivision of data science.

This course is fun and exciting, but at the same time, we dive deeper into machine learning. It is organized as follows:

Part 1 - Data pre-processing

Part 2 - Regression: Simple line regression, Multiple line regression, Multiple regression, SVR, Decision tree regression, Random forest regression

Part 3 - Rating: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

Part 4 - Clustering: K-sheath, classification clustering

Part 5 - Learn the Rules of Association: Apriori, Eclat

Part 6 - Learning Support: More Confidence, Thomson Model

Part 7 - Natural Language Processing: The Word Bag Model and the NLP Algorithm

Part 8 - Deep in Learning:- Artificial Neural Networks - Convolutional Neural Networks

Part 9 - Dimensions: PCA, LDA and Kernel PCA

Part 10 - Model Selection and Stability: K-Fold Cross Validation, Parameter Tuning, Network Search, XGBoost

In addition, the course is complete based on practical exercises based on real-life examples. So not only do you learn theory, but you also get practical training in modeling.

And as a bonus, this course includes the Python and R code templates that you can download and use in your projects.

Important updates (June 2020):

All icons today

Deep learning is encoded in TENSORFLOW 2.0.

Great gradient boosting models including XGBOOST and CATBOOST!

This course is for everyone:

  • Anyone interested in machine learning.
  • Students who have at least high school math knowledge and want to learn machine learning.
  • Anyone at the intermediate level wants to know more about the basics of machine learning, including classic algorithms such as linear regression or logistic regression, and wants to explore all the different areas of machine learning.
  • Anyone who is not comfortable with coding but is interested in machine learning and wants to easily apply it to data sets.
  • Any college student who wants to start a career in data science.
  • Any data analyst who wants to excel in machine learning.
  • Anyone who is not satisfied with his work & wants to become the data scientist.
  • Anyone who wants to add value to their business using powerful machine learning tools

Here is the download links

* If your in trouble watch the video thanks! *

Torrent software for windows -> Torrent Downloader

you can join over whats app group ->  FREE COURSES 2022

here my friend if you are looking for something you dont find please do comment and give advice or suggestion for more improvements

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here my friend if you are looking for something you dont find please do comment and give advice or suggestion for more improvements

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