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Machine Learning Basic to Advanced - Self Paced

Self-Paced Course
interested count56k+ interested Geeks

Course Description

This beginner to advanced level Machine Learning- Self Paced Course will help you learn all about ML, Data Processing, NLP & all other important topics. Also includes Machine Learning projects for a hands on learning experience.
levelBeginner to Advance
Lifetime AccessComprehensive LearningIndustry ReadinessCapstone Projects

Course Overview

Machine Learning is one of the most exciting technologies that one would ever come across. As is evident from the name, it is the technology that gives a program: The ability to learn. But even the machines cannot start learning on their own. Right? This is where YOU come in! Learn more about what machine learning is.

This Machine Learning Self-Paced Course will help you get started with the basics of ML, before moving on to advanced concepts. You will start off by getting introduced to topics such as: What is ML, Data in ML, and other basic concepts required to help build a strong base. You will get also get introduced to other important ML and AI concepts such as Regression, Classification, Clustering and will get to learn all about NLP. This self-paced course now also includes a host of real life Projects, which will give you real-time exposure on the topics of Sentiment Analysis, GDP Analysis, Text Encoding Decoding, Text Summarisation, among many others.

Mentored by industry experts who have years of experience in ML and many industry-based projects, you will surely go on to create a name for yourself in the field of Data Science and Artificial Intelligence. So wait no more, enter the world of AI and ML today!

Pre-requisite: Basics of Python Programming Language.

Once you are done with this self paced ML Course, it is recommended for you to check out Data Science-Live Classes and advance your career as a data scientist!
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Three 90 Challenge

90 Days

What you will learn


What you will learn

  • How to handle data efficiently 

  • Python tools related to Data Science

  • Complete Mathematical understanding of Machine Learning

  • Application of Machine Learning Models to solve real-life problems

Course Content

01Machine Learning Understanding

Get answers to all Machine Learning related questions, What is ML, Data in ML, Anaconda, Jupyter Notebook etc

02Handling Data

Learn about Numpy, Pandas, Matplotlib, Array Dimension, Categorical Data, Data Splitting, Data Scaling, Handling Missing Data etc 


Learn about Linear Regression, Polynomial Linear Regression, Support Vector, Decision Tree, Random Forest etc


Know all about Logistic Regression, K-NN Intuition & Code , Naive Bayes, Decision Tree Intuition, Decision Tree code, Random Forest Code, etc

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