Machine Learning and its Applications with Python - Online Mode

Who should attend

The programme is open to the faculty of engineering colleges, degree colleges, MCA colleges and other allied disciplines in India.

Course Content

• Introduction
• What is Machine Learning, Real-life examples
and Applications
Machine Learning vs. Data Science vs. AI,
Machine Learning types,
Generics of ML approaches. • Python Essentials
• Installation,
Python Editors & IDE's (Anaconda, Spyder, Jupyter),
Primitive Data types, lists,
tuples, dictionaries, strings,
Data manipulation tools (Operators, Functions,
Packages, Loops, arrays, etc.),
Importing Data from various sources
(CSV, txt, etc.) , Exporting Data to various formats.
• Probability and Statistics for Data Science
• Basic probability theory,
Random variables, Probability distributions,
Markov models, Bayesian learning, Applications.
• Regression
Univariate linear regression,
Multivariate linear regression,
Polynomial Regression, Applications.
• Classification
Logistic regression,
SVM, Multi-class SVM, Decision trees,
K-NN, Applications.
• Ensemble Approaches
• Bagging, Random Forests,
Boosting: Adaboost,
Gradient boosting, Applications.
• Optimization: Gradient descent,
Stochastic gradient descent,
Batch gradient descent.
• Clustering:
Different clustering approaches and applications.
• Feature Engineering
• Feature Scaling, Feature Selection:
Filter methods, Wrapper methods,
Embedded methods.
• Dimensionality Reduction:
PCA, LDA, MDA, ICA
• Reinforcement learning
• ML applications in Computer Vision,
Recommendation Systems
• Hands-on to the majority of
the topics using Python,
Take-home project.

Registration Fee

Faculty and Research Scholars	Rs. 750/-
Industry Participants	Rs. 2250/-

The Participants need to pay the Registration Fee Online using the following details:
On-line Mode:
Account Name: Electronics & ICT Academy NITW
Account No: 62423775910
IFSC Code: SBIN0020149

How to Apply

Participants are required to fill the online registration form by clicking on the following link:

Registration Link:
https://forms.gle/BWCWkzpxcAfBuSwS9