Machine Learning: Making computers think!
- Basic Knowledge of python programming
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.
- About Me01:31
- Introduction to machine learning02:42
- Supervised vs Unsupervised learning03:04
- Setting up Environment02:28
- Installing dependencies01:54
- Setting up jupyter notebook01:35
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.
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.