Python Best Courses

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

Machine Learning A-Z™: Hands-On Python & R In Data Science Course Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
Machine Learning A-Z™: Hands-On Python & R In Data Science Course Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.

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

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

What you’ll learn

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

  • Master Machine Learning on Python & R
  • Have a great intuition of many Machine Learning models
  • Make accurate predictions
  • Learn how to make a 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
  • Handle advanced techniques like Dimensionality Reduction
  • Know which Machine Learning model to choose for each type of problem
  • Build an army of powerful Machine Learning models and know-how to combine them to solve any problem

Requirements

  • Just some high school mathematics level.

Description

Interested in the field of Machine Learning? Then this course is for you!
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. Machine Learning A-Z

This course is fun and exciting, but at the same time, we dive deep into Machine Learning.

  • Part 1 – Data Preprocessing
  • Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
  • The 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
  • Part 5 – Association Rule Learning: Apriori, Eclat
  • The Part 6 – Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
  • Part 7 – Natural Language Processing: Bag-of-words model and algorithms for NLP
  • Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
  • The Part 9 – Dimensionality Reduction: PCA, LDA, Kernel PCA
  • Part 10 – Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost
So not only will you learn the theory, but you will also get some hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects. Machine Learning A-Z

Who this course is for:

  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any students in college who want to start a career in Data Science.
  • Who any data analysts who want to level up in Machine Learning.
  • Any people who want to create added value to their business by using powerful Machine Learning tools.
  • Content From: https://www.udemy.com/course/machinelearning/
  • Python 3 Data Science – Time Series with Pandas
  • Last updated 1/2020
Download Tutorial Button