Data Science with Machine Learning Techniques Using Tensorflow-Internship cum Training

Last date to Enroll: 26th September 2021 Registration Fee: INR 1200

ABOUT THE INTERNSHIP CUM TRAINING PROGRAM:

ProjectContest.com (Project Contest Innovations LLP) in association with various Industries across India has taken the initiative to provide the Training cum Internship on the emerging areas to students, faculty, research scholars & startups for enhancing the skills for Employability & Entrepreneurship. So far through this initiative over 1000+ students from 70+ institution got benefited. In this regards now ProjectContest.com with Nandha InfoTech has planned to provide a 2 month(60 days) Training cum Internship focusing on "Data Science with Machine Learning Techniques Using Tensorflow".


ABOUT INDUSTRY:

Nandha Infotech a Web design company in Coimbatore who follows customer centric approach to business and website creation and ensure that our customers make money out of their solutions provided. Nandha Infotech is an ISO 9001:2015 certified company runned by a World Record Holder. Nandha Infotech not only develops software but also trains fresh minds of the society in various streams. Thus far, we have trained more than 1,00,000 youngsters around the world, making various achievements in various streams till date.

Website: www.nandhainfotech.com

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ABOUT THE INTERNSHIP:

Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.

In this training, you will learn popular machine learning algorithms, principle component analysis, and regularization by building a movie recommendation system. You will also learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendatio