What you’ll learn
Context of machine learning in today’s business world
Understanding machine learning life cycle
Techniques used in various phases of ML life cycle
Core understanding of ML algorithms
Implementation of ML algorithms
Model interpretation & optimization
he reasons in this course – Why to learn ML?
Let us find the path of ML learning – What to learn in ML?
Let us find the way of ML learning – How to learn ML?
In my 28 years of experience in software field, machine learning is one of my most exciting techno- managerial area to work and teach. In my opinion this skill will be the need of most of the business stake holders in every field. Machine learning is the core component of Artificial Intelligence and Data Science.
That’s why, in this course we will be learning core concepts of various algorithms in in simple language. You need good understanding of algorithms/models for correct implementation of it. Also, that will help in effective Optimization, Interpretation and Communication of the output of the model to various stake holders.
In this course, you will understand the various steps of model implementation in Python.
This course lectures consists of many supervised and unsupervised algorithms like Regression, Logistic regression, KNN, SVM, Naïve Bayes, Decision Tree, Random Forest, K-Means, Hierarchical clustering, etc. with core concepts and Python implementation of various ML life cycle.
So are you thrilled…..then why are you waiting for…. Let us explore this course….
- Executives, software developers, Analysts who are in the transition of evolving career of Machine learning
- Students to jumpstart in exciting and lucrative future of Machine learning
- Managers to upgrade their skills in this demanding Machine learning field
- Academics for understanding core concepts of Machine learning