Learn Artificial Neural Network From Scratch in Python
Created by Sachin Kafle | Published 4/2021
Duration: 18h 13m | 8 sections | 68 lectures | Video: 1280x720, 44 KHz | 5.8 GB
Genre: eLearning | Language: English + Sub

The MOST in-depth look at neural network theory, and how to code one with pure Python and Numpy

What you'll learn
Code a neural network from scratch in Python and numpy
Learn the math behind the neural networks
Get a proper understanding of Artificial Neural Networks (ANN) and Deep Learning
Derive the backpropagation rule from first principles
Describe the various terms related to neural networks, such as "activation", "backpropagation" and "feedforward"
Learn to evaluate the neural network models

Requirements
Basic math - some essential parts will be covered in the course itself so to make course beginner friendlyLinear and Logistic RegressionBasic understanding of classification and Regression problems
Description
Welcome to the course where we will learn about Artificial Neural Network (ANN) From Scratch!
If you're looking for a complete Course on Deep Learning using ANN that teaches you everything you need to create a Neural Network model in Python?
You've found the right Neural Network course!
After completing this course you will be able to:
Identify the business problem which can be solved using Neural network Models.
Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc.
Create Neural network models in Python and ability to optimize the model tuning hyper parameters
Confidently practice, discuss and understand Deep Learning concepts

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