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Learn Artificial Neural Network From Scratch in Python

The MOST in-depth look at neural network theory, and how to code one with pure Python and Numpy
4.7
4.7/5
(3 reviews)
2,077 students
Created by Sachin Kafle

9.6

CourseMarks Score®

10.0

Freshness

8.4

Feedback

9.8

Content

Platform: Udemy
Price: $11.99
Video: 18h 13m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

9.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 4/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.4 / 10
We analyzed factors such as the rating (4.7/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.8 / 10
Video Score: 10.0 / 10
The course includes 18h 13m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
15 resources.
0 exercise.
0 test.

Table of contents

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
This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks right out of the gate using Python and Numpy. All the materials for this course are FREE.
You should take this course if you are interested in starting your journey toward becoming a master at deep learning, or if you are interested in machine learning and data science in general. We go beyond basic models like logistic regression and linear regression and I show you something that automatically learns features.
What is covered in this course?
This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems.
Below are the course contents of this course on ANN:
•Part 1 – Python basics
This part gets you started with Python and learn the brush up the basics like data structures, comprehensions, Object Oriented Programming and so on.
This part will help you set up the python and Jupyter environment on your system and it’ll teach you how to perform some basic operations in Python. We will understand the importance of different libraries such as Numpy, Pandas, Seaborn and matplotlib libraries.
•Part 2 – Theoretical Concepts
This part will give you a solid understanding of concepts involved in Neural Networks.
In this section you will learn about the neurons and how neurons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model.
•Part 3 – Creating Regression and Classification ANN model in Python and R
In this part you will learn how to create ANN models in Python.
We will learn how to model the neural network in two ways: first we model it from scratch and after that using scikit-learn library.
•Part 4 – Tutorial numerical examples on Backpropagation
One of the most important concept of ANN is backpropagation, so in order to apply the theory we learnt in lecture session in the real world neural networks, we are going to execute backpropagation taking one numerical example. We are going to take the help of partial differentiation and update the weights in backpropagation using gradient descent algorithms.
By the end of this course, your confidence in creating a Neural Network model in Python will soar. You’ll have a thorough understanding of how to use ANN to create predictive models and solve business problems.

Requirements

• Basic math – some essential parts will be covered in the course itself so to make course beginner friendly
• Linear and Logistic Regression
• Basic understanding of classification and Regression problems

You will 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

This course is for

• Students interested in machine learning – all the concepts are given through three sessions: Lecture, Tutorial and Coding sessions
• Students who want to learn the mathematics behind neural networks which in turn will make you ninja in ANN
• Students who want to prefer learning the core of neural networks rather than learning how to do it with libraries

How much does the Learn Artificial Neural Network From Scratch in Python course cost? Is it worth it?

The course costs $11.99. And currently there is a 87% discount on the original price of the course, which was $94.99. So you save $83 if you enroll the course now.

Does the Learn Artificial Neural Network From Scratch in Python course have a money back guarantee or refund policy?

YES, Learn Artificial Neural Network From Scratch in Python has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Learn Artificial Neural Network From Scratch in Python course, but there is a $83 discount from the original price ($94.99). So the current price is just $11.99.

Who is the instructor? Is Sachin Kafle a SCAM or a TRUSTED instructor?

Sachin Kafle has created 15 courses that got 2,081 reviews which are generally positive. Sachin Kafle has taught 121,837 students and received a 4.2 average review out of 2,081 reviews. Depending on the information available, Sachin Kafle is a TRUSTED instructor.

More info about the instructor, Sachin Kafle

Founder of CSAMIN & Bit4Stack Tech Inc. [[Author, Teacher]]
Sachin Kafle is a Python and Java developer, ethical hacker and social activist. His interest’s lies in software development and integration practices in the areas of computation, quantitative fields of trade. His technological interests include Python, C, Java, C# programming. He has been involved in teaching since 2013.Sachin is a engineer of Computer Science (B.E. Computer Science). He is also an instructor on his previously made some geek Youtube channel. He has been giving free classes mostly for students who have not been able to pay for expensive classes in his country.

9.6

CourseMarks Score®

10.0

Freshness

8.4

Feedback

9.8

Content

Platform: Udemy
Price: $11.99
Video: 18h 13m
Language: English
Next start: On Demand

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