At the end of this course, you will be able to:
Upon successful completion of the course, the learner will be able to
Develop a good understanding of the fundamental concepts of Machine Learning
Gain skills in working with algorithms that underpin popular machine learning techniques
Build expertise on the underlying mathematical relationships within and across Machine Learning algorithms
Explore the paradigms of supervised and unsupervised learning
Acquire hands-on experience of working with various machine learning algorithms in a range of real-world applications
In this module you will learn how to perform the task to predict a dependent variable value based on a given independent variable using Linear regression.
In this module you will learn how to perform the task to predict a dependent variable value based on a given independent variable using Logistic regression and how the Logistic regression becomes a classification technique.
In this module you will learn how to create a tree-like model of decisions using Decision Tree algorithm.
In this module you will learn how to compare different machine learning algorithms, and choose the best one.
In this module you will learn how to create a Neural Network Model and use it for predicting the class.
In this module you will know how a learned SVM model representation can be used to make predictions for new data.
In this module you will learn how to build a classification algorithm consisting of many decisions trees.
Learning through E-Box is completely Hands-on and practice based thereby helping you understand the intricacies of Live Project Scenarios
E-Box’s programs and Courses are designed by Professionals in the Industry & Academicians, assuring a quality learning experience
With 100’s Mentors online ready to get your Doubts clarified and to Hand Hold you, you will always have someone to sort things our for you
All our Mentors are Top Professionals from their respective Industries. In E-Box you Learn and get mentored by professionals
Auto Evaluation is the Core of E-Box. Your solutions and answers are evaluated instantaneously by E-Box, thereby saving learners a lot of time
With Auto - Evaluation being the core of the Platform, E-Box uses AI & ML to assist Learners during their course of Study
E-Box’s AI algorithms provide you with Exercises that are Personalised and Adaptive based on your Interest and Calibre
Data becomes the core for evolving a personalised learning. E-Box uses these metrics for an Auto Corrective Learning Process