MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 937 MB | Duration: 2h 28m
What you'll learn
Fundamental Machine Learning & Deep Learning
Linear Regression, Logistic Regression, Perceptron and Neural Network
Detailed explanation about the four ML & DL models
Why Neural Networks are better?
Requirements
Basic Mathematics
Description
Why this Course?
Lot of us might have experienced difficulty when relating Machine Learning and Deep Learning models. This course aims to answer usual doubts such as,
Why Deep Learning?
Why Neural Network performs better than Machine Learning models?
Deep Learning and Machine Learning are totally different technologies or they are much related?
How Deep Learning evolved from Machine Learning?
What it Covers?
The course covers Machine Learning models such as Linear Regression, Perceptron, Logistic Regression and a Deep Learning model Dense Neural Network.
The four chapters (videos) of the course deal with the adult life of a Legend named Mr. S and show how he used the Machine Learning and Deep Learning models to solve interesting problems such as partying, dating, searching for soulmate and eventually marrying the suitable girl in his life.
Through the journey of Mr. S, you will finally get to know why Neural Network performs better & how Machine Learning and Deep Learning are related.
Videos contain interesting scenarios with simple numerical examples and explanations.
Who can opt for this Course?
This course will be highly useful for those individuals,
Who does/doesn't have CS background and wants to understand Deep Learning technically without coding & too much mathematics.
Who are getting started with Machine Learning or Deep Learning.
Who seeks the answer: Why Neural Network perform better than Machine Learning models and how Deep Learning evolved from Machine Learning.
Who does research AI and have fundamental doubts about functionality of Neural Networks.
Who this course is for:
Beginners who are curious about AI, Data Science, Machine Learning & Deep Learning
Researchers who want to understand the fundamentals clearly
Professionals who are eager to understand the capability & functionality of a Neural Network
Non-CS professional who wants to exploit ML and DL
Screenshots
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