Machine Learning: Making computers think!

A concise guide to getting started with machine learning.
Free tutorial
Rating: 4.6 out of 5 (235 ratings)
17,044 students
1hr 49min of on-demand video
English
English [Auto]

Machine learning
Prediction Models
Scikit learn
Python
Numpy
Pandas
Matplotlib

Requirements

  • Basic Knowledge of python programming

Description

This is a practical machine learning course for people who wan to kickstart their career in Machine learning. This course will give you an understanding of what is machine learning and the concepts related to it.  The course is structured in the following way:

  • Part1 - Introduction and setting Up environment

  • Part2 - Data Collection

  • Part3 - Data Analysis and Visualization

  • Part4 - Data Preprocessing

  • Part5 - Data Modelling

  • Part6 - Model Validation

  • Part7 - Ensemble Learning

  • Part8 - Dimensionality reduction

  • Part9 - Outro

At the end of this course you will learn how to create a simple pipeline for a prediction model and make it feasible for real time deployment.

Who this course is for:

  • Beginner Python developers curious about Machine learning.
  • Beginner data scientists.

Instructors

Aiming to help students build their development skills.
DSC VIT Powered by Google Developers
  • 4.1 Instructor Rating
  • 1,781 Reviews
  • 68,172 Students
  • 4 Courses

About us

A Google Developers' program for university students aimed at giving young developers a platform to learn, a community to implement, and a stage to teach.

Inspiring minds and guiding talent, we believe in technical empowerment of all. We promote curiosity and cultivate projects in order to inculcate productivity aimed at achieving the growth of both the dev community as well as the world.

Machine Learning Engineer and deep learning enthusiast
Ubaid Usmani
  • 4.6 Instructor Rating
  • 235 Reviews
  • 17,044 Students
  • 1 Course

Python developer and Machine learning engineer.

Currently interning as a NLP engineer at LegalMind and a backend developer in python at Howitzer's Technology.

Previously worked as ML intern at Tata consultancy services.

I am an active technical committee member at Developer Student Clubs VIT, mentor at ACM VIT and a volunteer at GirlScript foundation.

My current hobby includes building and optimizing machine learning models and deploying them into real time tangible products. 

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