Learn Machine Learning — all in less than 40 hours.
Machine Learning is a sub-field of Artificial Intelligence (AI) that enables computer systems to learn and improve at performing a wide range of tasks without the need to be explicitly programmed.
It has gained immense popularity over the last few decades due to many reasons such as the rise in computational power, generation of more volume of data, discovery of new implementation use cases, etc.
In this ‘Machine Learning Fast-Track’, you will learn the A-Z of Machine Learning including how to implement Machine Learning algorithms programmatically.
Ready to start learning?
1. Linear Algebra Fundamentals – Refresher Course
Take this mini-course to go through a quick refresher on the basic concepts of Linear Algebra.
2. Supervised Machine Learning with Python
Learn to build multiple types of Supervised Machine Learning models using Python.
3. Theory of Deep Learning – Deep Neural Networks
Learn the theory behind how Deep Neural Networks work through mathematical examples.
4. Convolutional Neural Network Theoretical Course
Learn the theory behind Convolutional Neural Networks and understand how to build one.
5. TensorFlow – Hands-on Machine Learning with TF
Learn TensorFlow by building multiple Machine Learning projects through a hands-on approach.
6. TensorFlow JS – Build ML Projects using Javascript
Learn TensorFlow.js and build Machine Learning projects for the web using Javascript.
7. Natural Language Processing (NLP) using NLTK with Python
Learn to perform basic Natural Language Processing (NLP) tasks using NLTK.
8. Time-Series Forecasting with TensorFlow 2.0
Learn to build powerful time-series forecasting model using various deep learning algorithms.
9. Face Mask Detection using Machine Learning and Python
Learn to create Supervised and Unsupervised Machine Learning Algorithms from two proven Data Science experts.
Fast-Track Extra Courses and Resources
Full-Stack Data Science Course – Become a Data Scientist
Master the four major areas of Data Science and become a Full Stack Data Scientist using Python.
Data Science for Sports – Sports Analytics
Deep dive into the world of sports analytics and visualization with Python.
Data Science for Business Analytics and Intelligence
Use Google Analytics data to discover ways to unlock valuable business insights.
Customer Analytics for Businesses: Crash Course
Gain the skills required to use customer data in order to extract information and curate strategies.
Data Science for E-commerce: Crash Course
Learn how data science can be used in the e-commerce industry through this complete crash course.
Recommender Systems for Beginners
Learn how to build intelligent Recommender Systems for businesses as a beginner.
