Beginners Guide To Deep Learning 2022

Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. Deep learning is getting lots of attention lately and for good reason. It's achieving results that were not possible before.Deep Learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over without being programmed to do so.In data science, an algorithm is a sequence of statistical processing steps. In machine learning, algorithms are 'trained' to find patterns and features in massive amounts of data in order to make decisions and predictions based on new data. The better the algorithm, the more accurate the decisions and predictions will become as it processes more data.Deep Learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.

Overview
Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Before you start!!

Lecture 3 Setting up Google Colab

Section 2: Building Theoretical Concept

Lecture 4 Neurons Explained!

Lecture 5 Introduction to neural network

Lecture 6 Introduction to Activation Function

Section 3: Building Practical Concept

Lecture 7 Introduction to tensor

Lecture 8 Real World Tensor Example

Lecture 9 Tensor Operations

Lecture 10 Introduction to Gradient Optimization

Lecture 11 Gradient Optimization in detail

Lecture 12 BackPropagation

Lecture 13 Example of Neural Network

Section 4: Getting started with Neural Network

Lecture 14 Introduction to the section

Lecture 15 Anatomy of Neural Network

Lecture 16 Quick Overview of Keras

Lecture 17 Movie Review Classification Problem

Lecture 18 Classifying NewsWire

Lecture 19 Predicting House Price

Students who wants to learn about Deep Learning,Machine-learning enthusiasts,Data scientists who want to expand their library of skills,Scientists and researchers interested in deep learning

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