Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.81 GB | Duration: 9h 31m
Learn how to create state of the art neural networks for deep learning with Facebook’s PyTorch Deep Learning library!
What you’ll learn
Pandas
Pytorch
Numpy
Artificial Neural Networks (ANN)
Generative adversarial network (GAN)
Convolution Neural Network (CNN)
Recurrent Neural Network (RNN)
Google Colab .
Matplotlib.
Long Short Term Memory (LSTM)
Language Model
Reinforcement Learning
OpenAI Gym
Requirements
There will be no Prerequisites.
Basic knowledge of Python will be good.
But everything will be taught from the round up.
Description
Welcome to the best online course for learning about Pytorch!
Although Google’s Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence.
Is it possible that Tensorflow is popular only because Google is popular and used effective marketing?
Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems?
It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab – FAIR). So if you want a popular deep learning library backed by billion dollar companies and lots of community support, you can’t go wrong with PyTorch. And maybe it’s a bonus that the library won’t completely ruin all your old code when it advances to the next version. ?
On the flip side, it is very well-known that all the top AI shops (ex. OpenAI, Apple, and JPMorgan Chase) use PyTorch. OpenAI just recently switched to PyTorch in 2022, a strong sign that PyTorch is picking up steam.
In this course you will learn everything you need to know to get started with Pytorch, including
NumPy
Pandas
Tensors with PyTorch
Neural Network Theory
Perceptrons
Networks
Activation Functions
Cost/Loss Functions
Backpropagation
Gradients
Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
and much more!
By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.
So what are you waiting for? Enroll today and experience the true capabilities of PyTorch! I’ll see you inside the course!
Who this course is for
Anyone interested in Machine Learning.
Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence.
Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
Any students in college who want to start a career in Data Science
Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
Any people who are not satisfied with their job and who want to become a Data Scientist.
Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.
Any people who want to create added value to the local hospital by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools.
Any people who want to work in healthcare field as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.
Any people who want to work in a Taxi Company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.
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