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Robot on Wheels

Advance Machine Learning

The science of training machines to perform functions without being directly programmed is
known as “Machine learning (ML)”. Self-driving vehicles, usable voice recognition, efficient online search, and several other humans like intelligent task have all been made possible by ML in the past few decades. ML is so popular these days that you actually use it hundreds of times a day without even understanding it. Many scientists believe that it is the most effective way to provide intelligence in machines to make their functioning closer to a human. This internship will make you learn about the most powerful machine learning methods and give you best exposure in applying them for industrial purposes. More specifically, you will learn not only about the theoretical foundations of ML but also how to adapt these methods to new challenges easily and effectively. Apart from this you will learn about the best practices of innovative machine learning and AI.

This internship will provide you a comprehensive introduction to machine learning, approaches of Data mining, and statistical pattern recognition. You will understand and apply the techniques of supervised learning such as parametric/non-parametric algorithms, support vector machines (SVM) classifier, kernels, neural networks (KNN). Unsupervised learning approach such as clustering, recommendation systems etc. will also be discussed. Best practices of ML such as bias/variance theory, innovation process in machine learning and AI are covered through rigorous coding exercises. In this internship you will apply ML in several industrial case studies and applications, so that you'll also learn how to apply ML algorithms to building smart robots, text understanding such as web search, medical informatics etc.

 Course fee: 5999 (INR)

Duration: 1 Months, 7-8hrs/Week

 Course fee: 2999 (INR)

Duration: 15 Days, 7-8hrs/Week

Week 1
Introduction to ML and linear regression will be discussed. You will develop projects based on linear regression. Basics of cost function and the gradient descent method for learning will also be discussed.
Week 2
This week we will focus on logistic Regression, regularization, neural networks, backpropagation algorithm. In this week, we will share the best industrial practices for employing ML in regular practice.
Week 3
To develop a ML algorithm, you must first identify the areas where the most significant changes must be made. You will learn how to interpet the output of a machine learning system with multiple components, as well as how to work with distorted results. Support vector machine (SVM) based classification tasks and project work will be assigned.
Week 4
Last week of this internship is dedicated to unsupervised learning to build models, clustering techniques that enable us to learn groupings of unlabeled data points. In this week, you will be encountered with the application of principal components analysis, and data compression techniques to speed up ML algorithms. You will also learn to design automatic recommender systems.

Apply only if you really want to work

Online, Work from Home
Industry Projects Only
Bring Your Idea Sessions
Instructor led Training
30+ Hours of Interaction 
One Mandatory Blog
Industry Ready check
Placement Assistance 
Special Monitory Award for Star performers
Financial Aid Available 
Weekend / Evening Classes for IT Professionals & College Students
Resume Building
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