Machine Learning | Natural Language Processing | Streamlit
Last updated 12/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.15 GB | Duration: 14h 21m

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
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