Deep Learning and NLP AZ How to create a ChatBot

Learn the Theory and How to implement state of the art Deep Natural Language Processing models in Tensorflow and Python
Deep Learning and NLP AZ How to create a ChatBot
File Size :
9.74 GB
Total length :
12h 9m

Category

Instructor

Hadelin de Ponteves

Language

Last update

Last updated 12/2022

Ratings

4.2/5

Deep Learning and NLP AZ How to create a ChatBot

What you’ll learn

Why this is important
Types of Natural Language Processing
Classical vs. Deep Learning Models
End to End Deep Learning Models
Seq2Seq Architecture & Training
Beam Search Decoding

Deep Learning and NLP AZ How to create a ChatBot

Requirements

Just some high school mathematics level
Basic Python programming knowledge

Description

We’ve talked about, speculated and often seen different applications for Artificial Intelligence – But what about one piece of technology that will not only gather relevant information, better customer service and could even differentiate your business from the crowd?
ChatBots are here, and they came change and shape-shift how we’ve been conducting online business. Fortunately technology has advanced enough to make this a valuable tool something accessible that almost anybody can learn how to implement.If you want to learn one of the most attractive, customizable and cutting edge pieces of technology available, then this course is just for you!

Overview

Section 1: Welcome to the course!

Lecture 1 Get Excited!

Lecture 2 Applications

Lecture 3 Learning Paths

Lecture 4 Some Additional Resources!!

Lecture 5 This PDF resource will help you a lot!

Lecture 6 Your Shortcut To Becoming A Better Data Scientist!

Lecture 7 Study Tips For Success

Section 2: Deep NLP Intuition

Lecture 8 What You’ll Need For This Module

Lecture 9 Plan of Attack

Lecture 10 Types of Natural Language Processing

Lecture 11 Classical vs Deep Learning Models

Lecture 12 End-to-end Deep Learning Models

Lecture 13 Bag-of-words model

Lecture 14 Seq2Seq Architecture (Part 1)

Lecture 15 Seq2Seq Architecture (Part 2)

Lecture 16 Seq2Seq Training

Lecture 17 Beam Search Decoding

Lecture 18 Attention Mechanisms (Part 1)

Lecture 19 Attention Mechanisms (Part 2)

Section 3: Building a ChatBot with Deep NLP

Lecture 20 ChatBot – Step 1

Lecture 21 ChatBot – Step 2

Lecture 22 ChatBot – Step 3

Section 4: ———- PART 1 – DATA PREPROCESSING ———-

Lecture 23 Welcome to Part 1 – Data Preprocessing

Lecture 24 ChatBot – Step 4

Lecture 25 ChatBot – Step 5

Lecture 26 ChatBot – Step 6

Lecture 27 ChatBot – Step 7

Lecture 28 ChatBot – Step 8

Lecture 29 ChatBot – Step 9

Lecture 30 ChatBot – Step 10

Lecture 31 ChatBot – Step 11

Lecture 32 ChatBot – Step 12

Lecture 33 ChatBot – Step 13

Lecture 34 ChatBot – Step 14

Lecture 35 ChatBot – Step 15

Lecture 36 ChatBot – Step 16

Lecture 37 ChatBot – Step 17

Lecture 38 Checkpoint!

Section 5: ———- PART 2 – BUILDING THE SEQ2SEQ MODEL ———-

Lecture 39 What You’ll Need For This Module

Lecture 40 Welcome to Part 2 – Building the Seq2Seq Model

Lecture 41 ChatBot – Step 18

Lecture 42 ChatBot – Step 19

Lecture 43 ChatBot – Step 20

Lecture 44 ChatBot – Step 21

Lecture 45 ChatBot – Step 22

Lecture 46 ChatBot – Step 23

Lecture 47 ChatBot – Step 24

Lecture 48 Checkpoint!

Section 6: ———- PART 3 – TRAINING THE SEQ2SEQ MODEL ———-

Lecture 49 What You’ll Need For This Module

Lecture 50 Welcome to Part 3 – Training the Seq2Seq Model

Lecture 51 ChatBot – Step 25

Lecture 52 ChatBot – Step 26

Lecture 53 ChatBot – Step 27

Lecture 54 ChatBot – Step 28

Lecture 55 ChatBot – Step 29

Lecture 56 ChatBot – Step 30

Lecture 57 ChatBot – Step 31

Lecture 58 ChatBot – Step 32

Lecture 59 ChatBot – Step 33

Lecture 60 ChatBot – Step 34

Lecture 61 ChatBot – Step 35

Lecture 62 ChatBot – Step 36

Lecture 63 Checkpoint!

Section 7: ———- PART 4 – TESTING THE SEQ2SEQ MODEL ———-

Lecture 64 What You’ll Need For This Module

Lecture 65 Welcome to Part 4 – Testing the Seq2Seq Model

Lecture 66 ChatBot – Step 37

Lecture 67 ChatBot – Step 38

Lecture 68 ChatBot – Step 39

Lecture 69 ChatBot – Step 40

Lecture 70 Checkpoint!

Lecture 71 Training the ChatBot on Google Colab with GPU

Section 8: ———- PART 5 – IMPROVING & TUNING THE SEQ2SEQ MODEL ———-

Lecture 72 ChatBot – Step 41: Improving & Tuning the ChatBot

Lecture 73 ChatBot – Step 42: Introduction to a new model & setup

Lecture 74 ChatBot – Step 43: Chatbot model discussion

Lecture 75 ChatBot – Step 44: Tensorboard

Lecture 76 ChatBot – Step 45: Run the new chatbot model

Section 9: Other ChatBot Implementations

Lecture 77 What You’ll Need For This Module

Lecture 78 The Best ChatBot

Lecture 79 A ChatBot Implementation in TensorFlow 1.4

Lecture 80 A ChatBot Implementation in PyTorch

Lecture 81 THANK YOU Video

Section 10: Annex 1: Artificial Neural Networks

Lecture 82 Plan of Attack

Lecture 83 The Neuron

Lecture 84 The Activation Function

Lecture 85 How do Neural Networks work?

Lecture 86 How do Neural Networks learn?

Lecture 87 Gradient Descent

Lecture 88 Stochastic Gradient Descent

Lecture 89 Backpropagation

Section 11: Annex 2: Recurrent Neural Networks

Lecture 90 Plan of Attack

Lecture 91 What are Recurrent Neural Networks?

Lecture 92 Vanishing Gradient Problems for RNNs

Lecture 93 Long Short Term Memory

Lecture 94 Practical Intuition

Lecture 95 Long Short Term Memory Variations

Section 12: Special Offer

Lecture 96 ***YOUR SPECIAL BONUS***

Any students in college who want to start a career in Data Science,Any Data Science enthusiast,Anyone interested in creating their own ChatBot,Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning and its applications

Course Information:

Udemy | English | 12h 9m | 9.74 GB
Created by: Hadelin de Ponteves

You Can See More Courses in the Developer >> Greetings from CourseDown.com

New Courses

Scroll to Top