Machine Learning | Natural Language Processing | Streamlit

With A Strong Foundation in ML & NLP, Build an NLP Web Application and host it!

What you'll learn

You will learn insights on Machine Learning and Artificial Intelligence concepts

You will understand the Math behind the Artificial Intelligence solutions

You will learn Time series and simple linear regression

You will learn Multiple & Logistic regression

You will learn decision tree & other advanced algorithms

You will work on an AI project using the AI & ML concepts learnt using this course

You will understand the theory behind Artificial Intelligence

Learn where AI and Machine learning algorithms are used today

Requirements

General awareness on Artificial intelligence and Machine learning and enthusiasm to learn the applications

Description

Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today's society. More specifically, it is Weak AI, the form of AI where programs are developed to perform specific tasks, that is being utilized for a wide range of activities including medical diagnosis, electronic trading platforms, robot control, and remote sensing. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more.Artificial intelligence has dramatically changed the business landscape. What started as a rule-based automation is now capable of mimicking human interaction. It is not just the human-like capabilities that make artificial intelligence unique. An advanced AI algorithm offers far better speed and reliability at a much lower cost as compared to its human counterparts.And the AI landscape is also changing.  You may be successful in completing an ML project but how will you demonstrate that to your clients? If you want to develop an AI application as a web application, how will you handle the user interface and how will you host the application? Streamlit helps to achieve these and many more.We start the program with basics and gradually build the tempo. In this course you will learn:Basics of AI - What is AI, What is Driving the rise of AIMachine Learning - Basics & AlgorithmsNatural Language Processing Build and Host an NLP application

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Understanding the AI ML Environment

Lecture 2 Introduction to AI

Lecture 3 Pattern Recognition

Lecture 4 Hardware revolution driving the rise of AI

Lecture 5 Introduction to Big Data

Lecture 6 Introduction to cloud

Lecture 7 Industrial Revolution 4.0

Lecture 8 ML Concepts

Section 3: Math & Stats Behind ML

Lecture 9 Central Tendency Vs Dispersion

Lecture 10 Dependent Vs Independent Variable

Lecture 11 Types of Data

Lecture 12 Sampling

Lecture 13 Hypothesis Testing

Lecture 14 Outliers

Lecture 15 Machine Learning Concepts

Lecture 16 Measuring Accuracy in Algorithms

Lecture 17 Math behind regression

Lecture 18 Math behind decision tree

Lecture 19 Math behind kNN

Lecture 20 Gradient Descent

Section 4: Python Programming

Lecture 21 Introduction to Python

Lecture 22 Arrays

Lecture 23 Loops & Conditions

Lecture 24 Numpy

Lecture 25 Pandas

Lecture 26 Matplotlib

Section 5: ML Programming

Lecture 27 Linear regression

Lecture 28 Logistic Regression

Lecture 29 Unsupervised Learning

Section 6: Natural Language Processing

Lecture 30 Key Concepts in NLP

Lecture 31 Ambiguities in NLP

Lecture 32 NLTK

Lecture 33 Noise Removal

Lecture 34 Spacy

Lecture 35 Flash Text

Lecture 36 Named Entity Recognition

Section 7: Build and Host ML Applications on the web

Lecture 37 Infrastructure for Streamli

Lecture 38 Creating a very simple web app and Getting started with streamlit

Lecture 39 Header and Sub Header

Lecture 40 Reading and displaying contents of a file

Lecture 41 Uploading a file

Section 8: Building & Deploying an NLP Wordcloud as a web application

Lecture 42 NLP Wordcloud App

Lecture 43 Deploying the app in Heroku

Lecture 44 Deploying the app in streamlit

Section 9: Machine Learning - ML Introduction

Section 10: Bonus Lecture

Lecture 45 Bonus Lecture

Students and Professionals interested in Artificial Intelligence and Machine Learning,Professionals who just started their career as Data Analysts and are keen to learn more,Students who are passionate about Artificial Intelligence and Machine learning and its applications