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Deep Learning and Neural Networks Python Keras
Build deep learning models with Python and Keras.
Development ,Data Science,Deep Learning
Lectures -88
Resources -4
Duration -11 hours
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Course Description
Deep Learning and Neural Networks Python Keras course is a basic to advanced crash course. The course teaches you deep learning neural networks and convolutional neural networks using Keras and Python. It is designed to skyrocket your current career prospects as this is the most in-demand skill today and for sure is the technology of the future.
Course Overview
The world has been revolving much around the terms "Machine Learning" and "Deep Learning" recently. With or without our knowledge every day we are using these technologies. There will be a day in the near future when deep learning models will outperform human intelligence.
Deep Learning and Machine Learning along with Data Science are a few of the most sought-after talents in the technology world nowadays. Its applications range from Google suggestions, translations, ads, movie recommendations, friend suggestions, sales and customer experience, and many more.
Learning these technologies involves a misconception that it needs prior knowledge of maths, statistics, complex algorithms, and formulas. The basic know-how is an added advantage but it is definitely not mandatory.
In this deep learning course, there is a perfect balance between learning the basic concepts along the implementation of the built-in Deep Learning Classes and functions from the Keras Library using the Python Programming Language.
These classes, functions, and APIs are just like the control pedals from the car engine, which we can use easily to build an efficient deep-learning model. Build deep learning models to solve a variety of problems, such as image classification, natural language processing, and speech recognition.
Goals
Understand the fundamentals of Neural Networks.
Master the basics of deep learning.
Understand the basics of machine learning.
Build and train deep learning models.
Use deep learning for problem-solving.
Prerequisites
A medium-configuration computer.
Willingness to learn in order to indulge in the world of deep learning.

Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
3 Lectures
-
Course Introduction and Table of Contents 11:29 11:29
-
Deep Learning Overview - Theory Session - Part 1 05:51 05:51
-
Deep Learning Overview - Theory Session - Part 2 06:30 06:30
Choosing Between ML or DL for the next AI project
1 Lectures

Preparing Your Computer
2 Lectures

Python Basics
4 Lectures

Environment Setup
8 Lectures

Explaining Multi-Layer Perceptron Concepts
1 Lectures

Explaining Neural Networks Steps and Terminology
1 Lectures

First Neural Network with Keras
1 Lectures

Explaining Training and Evaluation Concepts
1 Lectures

Pima Indian Model
8 Lectures

Iris Flower Multi-Class
4 Lectures

Sonar Returns Dataset
2 Lectures

Sonar Performance Improvement
3 Lectures

Boston Housing
2 Lectures

Boston Performance Improvement
3 Lectures

Pima Indian Dataset
4 Lectures

Load and Predict
3 Lectures

Checkpointing
4 Lectures

Plotting Model Behavior History
2 Lectures

Dropout Regularization
3 Lectures

Learning Rate Schedule using Ionosphere Dataset
1 Lectures

Time Based Learning Rate Schedule
2 Lectures

Drop Based Learning Rate Schedule
2 Lectures

Convolutional Neural Networks
2 Lectures

MNIST Handwritten Digit Recognition Dataset
2 Lectures

MNIST Multi-Layer Perceptron Model Development
2 Lectures

Convolutional Neural Network Model using MNIST
2 Lectures

Large CNN using MNIST
1 Lectures

Load and Predict using the MNIST CNN Model
1 Lectures

Augmentation
5 Lectures

CIFAR-10 Object Recognition Dataset
1 Lectures

Simple CNN using CIFAR-10 Dataset
3 Lectures

Train and Save CIFAR-10 Model
1 Lectures

Load and Predict using CIFAR-10 CNN Model
1 Lectures

SOURCE CODE ATTACHED
1 Lectures

Instructor Details

Abhilash Nelson
I am a pioneering, talented and security-oriented Android/iOS Mobile and PHP/Python Web Developer Application Developer offering more than eight years’ overall IT experience which involves designing, implementing, integrating, testing and supporting impact-full web and mobile applications.
I am a Post Graduate Masters Degree holder in Computer Science and Engineering.
My experience with PHP/Python Programming is an added advantage for server based Android and iOS Client Applications.
I am currently serving full time as a Senior Solution Architect managing my client's projects from start to finish to ensure high quality, innovative and functional design.
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