
Download and install Anaconda to set up a ready-to-use machine learning environment. Launch Jupyter or Spyder to run beginner-friendly machine learning examples and practice experimental setup.
Explore how support vector machines use hyperplanes to separate data, compare kernel options, and tune gamma and regularization to maximize margin for clear class separation.
Indicative Module Content
Introduction to Research - This session will help you to start the wonderful journey of research. Research is useful for finding new opportunities , new discoveries and higher studies
Finding a research problem - Finding a research problem is the most important aspect of any research project . (Undergraduate, Postgraduate etc..)
Finalizing your objectives-
Research Methodology
Positivism
Interpretivism
Introduction to Machine Learning:- What is Machine Learning ?, -> in this session we will get an overview of machine learning
Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google Collabs -
(All the instructions will be provided to setup the environment successfully.)
Artificial Neural networks [Theory and practical sessions - hands-on sessions] - This practical hands-on session will guide you to create a comprehensive ANN project
Machine Learning Techniques : Support Vector Machines - Lecture & Hands - On with Google Collabs ,
Trees and Random Forest - Lecture & Hands-On with Google Collabs,