Introduction to Machine Learning with Python (10 hours)
Python and Machine Learning Mastery >> Introduction to Machine Learning with Python (10 hours)
How
does Gmail’s spam classifier work? How does Google Photos automatically
organize your photos? How do chatbots work? How can we make sales forecasts?
How does Netflix recommend new shows for you to see? Can we write a chess
program that learns on its own? All of these applications depend on Machine
Learning. If you have wondered about how the modern AI and Machine Learning
revolution has affected our lives and how you can use it for your own
applications, our hands-on course “Introduction to Python and Machine Learning”
is for you.
As
the world moves more and more towards digital applications, Artificial
Intelligence will become an indispensable part of every company and product.
Our course will introduce you to popular machine learning algorithms used in a
variety of practical tasks. Not only will you learn about how these methods
work, you will also learn how to code them on your own and use them in your
applications.
At
the end of the course, you will be able to write Python programs using Machine
Learning frameworks for a range of practical problems -- House price
prediction, Spam classifier, image classification, Customer clustering, Book
recommender, etc. We will be introducing you to state-of-the-art algorithms for
these in a practical manner.
Syllabus
- What are
Artificial Intelligence and Machine Learning?
- Introduction to
Python and important libraries -- Numpy, pandas, etc
- Review of
useful mathematics
- Basics of Machine
Learning
- Learning Paradigm
- Handling Data
- The Machine Learning Pipeline
- Python
Frameworks for Machine Learning -- scikit-learn, keras, Tensorflow,
PyTorch
- Supervised
Learning with Applications.
a. Algorithms -- Linear regression, Logistic regression, Deep Neural
Networks, Decision Trees, etc
b. Numerical applications -- Price Prediction, Forecasting, etc
- Image Data applications -- Image
recognition
- Text data applications -- Sentiment analysis, Spam classifier
- Unsupervised Learning with Applications
a. Algorithms -- k-Means, DBSCAN, etc
b. Clustering algorithms -- Customer clustering, etc
c. Recommender systems -- Book and movie recommenders, etc
- A glimpse of
more advanced topics
Special features of the course
- The course will be offered in a mix of Tamil and
English so that language is not a barrier to understanding. (If there
is demand, a separate pure English version may also be created.)
- It will consist
of 10+ hrs of lecture videos with practical code walkthroughs.
- There will be
multiple unsolved exercises given for practice and to build your
confidence.
- An intensive
Final Project at the end of the course for your
self-assessment.
- An online Quiz to be taken at the end of the course for obtaining a certificate of completion.
Instructors -- The instructors
are Dr Ganapathy Krishnamurthi and Dr Balaji Srinivasan. Both of them are
faculty at IIT-Madras and are co-founders of Inuaid.
When -- The course
will be released SOON. The course will be delivered via recorded videos which you may watch at your own convenience.