Complete Data Science,Machine Learning,DL,NLP Bootcamp

Getting Started With VS Code

Different Ways of Creating Virtual Environment

Solve Conda Not Recognized Isssue

Python Basics-Syntax And Semantics

Variables In Python

Basics Data Types In Python

Operators In Python

Coding Excercise And Assignments

Conditional Statements (if, elif, else)

Loops In Python

Coding Excercise And Assignments

List And List Comprehension In Python

List Practice Code And Assignment

Tuple In Python

Tuple Assignment And Practise Code

Sets In Python

Sets Assignment and Practise Code

Dictionaries In Python

Dictionaries Assignments And Practise Questions

Real world Usecases Of List

Getting Started With Functions

More Coding Example With Functions

Lambda Function In Python

Map Function In Python

Filter Function In Python

Functions Assignments and Practise Content

Celsius To Fahrenheit

Area of a Rectangle

Distance Covered by a Vehicle

Number of Rounds of Lift

Line Equation

Sum of List Elements

Largest Element in a List

Remove Duplicate in a List

Check if all elements in a List are Unique

Reverse a List

Number of Odd and Even Elements in a list

Check if List is Subset of Another List

Maximum Difference between 2 consecutive elements in a List

Merge two sorted List

Rotate a List

Merge 2 list into Dictionary

Merge Multiple Dictionary

Words Frequency in a Sentence

Palindromic Tuple

Merge Dictionaries with Common Keys

Import Modules And Packages In Python

Standard Library Overview

Packages Assignment And Practise Questions With Solutions

File Operation In Python

Working With File Paths

File handling Operation Assignment With Solutions

Exception Handling With try except else and finally blocks

Exception Handling Practise Assignments And Solution

Classes And Objects In Python

Classes And Objects Practise Questions And Solutions

Inheritance In OOPS

Polymorphism In OOPS

Encapsulation In OOPS

Abstraction In OOPS

Practise Assignments With Solutions

Magic Methods In Python

Operator Overloading In Python

Custom Exception Handling

Complete OOPS Practise Question With Solutions

Iterators In Python

Generators With Practical Implementation

Function Copy,Cloures And Decorators

Advance Python Practise Questions And Solutions

Numpy In Python

Pandas- DataFrame And Series

Data Manipulation With Pandas And Numpy

Reading Data From Various Data Source Using Pandas

Data Visualization With Matplotlib

Data Visualization With Seaborn

Pandas And Numpy Assignments And Solutions

SQLITE3 Assignments And Solutions

Crud Operation With SQLite3 And Python

Logging Practical Implementation In Python

Logging With Multiple Loggers

Logging With A Real World Example

Logging Assignments And Solutions

What Is Process And Threads

2-Multithreading Practical Implementation With Python

Multiprocessing Practical Implementation With Python

Thread Pool Executor and Process Pool

Implement Web Scraping Usecase With Multithreading

Real World Usecase Implementation With MultiProcessing

Memory Allocation And DeallocationGarbage collection and Best Practises

Introduction To Flask Framework

Understanding Simple Flask App Skeleton

Integrating HTML With Flask Web App

Working With HTTP Verbs Get And Post

Building Dynamic Url ,Variables Rule And Jinja 2 Template Engine

Working With Rest API's And HTTP Verbs Put And Delete

Building Web App Using Streamlit

Example Of ML App With Streamlit Web App

What is Statistics And its Application

Types Of Statistics

Population Vs Sample Data

Measure Of Central Tendency

Measure Of Dispersion

Why Sample Variance Is Divided By n-1?

Standard Deviation

What Are Variables?

What are Random Variables

Histograms- Descriptive Statistics

Percentile And Quartiles- Descriptive Statistics

5 Number Summary-Descriptive Statistics

Correlation And Covariance

Addition Rule (For Mutual And Non Mutual Exclusive Events)

Probability-Multiplication Rule(Independent And Dependent Events)

The Relationship Between PDF,PMF And CDF

Types Of Probability Distribution

Bernoulli Distribution

Binomial Distribution

Poisson Distribution

Normal/ Gaussian Distribution

Standard Normal Distribution And Z Score

Uniform Distribution

Log Normal Distribution

Power Law Distribution

Pareto Distribution

Central Limit Theorem

Estimates

Hypothesis Testing And Mechanism

What is P value?

Z Test- Hypothesis Testing

Student t Distribution

T Stats With T test Hypothesis Testing

Z test Vs T test

Type 1 And Type 2 Error

Bayes Theorem

Confidence Interval And MArgin Of Error

What is Chi Square Test

ChiSquare Goodness OF Fit

Annova Test

Assumptions Of Annova

Types Of Annova

Partioning Of Variance In Annova

Handling Missing Values

Handling Imbalanced Dataset

Handling Imbalanced Dataset Using Smote

Handling Outliers Using Python

Data Encoding- Nominal Or OHE

Label And Ordinal Encoding

Target Guided Ordinal Encoding

Red Wine Dataset EDA

EDA And Feature Engineering Flight Price Dataset

Data Cleaning With Google Playstore Dataset

Part 2- EDA Google Play Store Cleaned Dataset

Introduction

Types of ML Techniques

Equation of Line, 3d, and Hyperplane

Distance of a point from a plane

Instance based Vs Model based learning

Simple Linear Regression Introduction

Understanding Simple Linear regression Equations

Cost Function

Convergence Algorithm

Convergence Algorithm Part02

Multiple Linear regression

Performance Metrics

MSE, MAE, RMSE

Overfitting and Underfitting

Linear Regression with OLS

Simple Linear Regression Practical

Multiple Linear regression

Polynomial Regression Intuition

Polynomial Regression Implementation

Pipeline in Polynomial

Ridge Regression

Lasso & ElasticNet

Types Of cross Validation

Cleaning the Dataset

EDA and Feature Engineering

Feature Selection

Model Training

Hyperparameter tuning

Basic Simple Linear Regression Project

Multiple Linear Regression Projects With Assumptions

Basic Regression Project From Scratch-EDA And Feature Engineering

Model Training With Cross Validation Using Lasso Regression

Model Training With Ridge and Elastic net With Cross Validation

Model Pickling In ML Project

End To End ML Project Implementation

Project Deployment In AWS

Can Linear Regression Solve Classifier Problem.

Logistic Regression Indepth Math Intuition

Performance Metrics

Logistic Regression OVR

Logistic Regression Implementation

Grid Search Hyper Parameter

Randomised Search CV

Logistic OVR

Logistic Imbalanced Dataset

Logistic Regression ROC

Introduction to support vector Machine

SoftMargin and Hard Margin

SVM Maths Intuition

SVC Cost function

Support Vector Regression

SVM Kernels

Support Vector Classifiers

SVM Kernels implementation

Support Vector Regression Implementation

Understanding Baye's Theorem

Variants Of Naive Baye's

Naive Baye's Practical Implementation

KNN Classification And Regression Indepth Intuition

Optimization Of KNN- KDtree And Ball Tree Indepth Intuition

KNN Classifier And Regressor Classification

Introduction TO Decision Tree.

Entropy and Gini Impurity

Information Gain

Entropy vs Gini impurity

Decision Tree Split for Numerical Features

Post Pruning & Pre Pruning

Decision Tree Regression

Decision Tree Implementation

Decision tree Prepruning

Diabetes Prediction Using Decision Tree Regressor

Bagging & Boosting Ensemble Techniques.

Random Forest Regression

Problem Classification

Feature Engineering Part 01

Feature Engineering Part 02

Model Training Step

Random Forest Regression Project-Problem Statement

Feature Engineering

Model Training

Introduction to Adaboost ML algorithm

Creating Decision Tree Stump

Performance of Decision Tree Stump

Updating Weights.

Normalising Weights and Assigning Bins

Selecting New Datapoints for Next tree

Final Prediction for Adaboost

Adaboost Model Training

Adaboost Regressor Model Training

Gradient Boosting Regression

Gradient Boost Classifier Training

Gradient Boost Regression Model Training

Xgboost Classification Indepth Intuit

Xgboost Regressor

Model Training Xgboost.

Xgboost Regressor Training

Introduction To Unsupervised Machine Learning

Curse Of Dimensionality

Feature Selection and Extraction

PCA Geometric Intuition

PCA Maths Intuition 01

Eigen Decomposition on Covariance Matrix

PCA Implementation

Kmeans Clustering Geometric Intuition

How to Find K Values?

Random Initialisation Trap(Kmeans++)

K means Clustering Implementation

Hierarichal Clustering

Agglomerative Clustering Implementation

Kmeans vs Hierarical Mean Clustering

How DBSCAN Works?

Examples After Applying DBSCAN

Pros and Cons Of DBSCAN

DBSCAN Clustering Implementation

Silhoutte Clustering Intuition

Anomaly Detection USsing Isolation Forest Indepth Intuition

DBSCAN Clustering Anomaly Detection

Local Outlier Factor Anomaly Detection

Dockers Series

Dockers and What is Containers

Docker image vs Containers

Docker vs Virtual Machines

Docker Installation

Docker Basic Commands

Creating a Docker Image

Push Docker Image to Docker Hub

Docker Compose

Introduction, Installation and Basic Commands

Git Merge, Push, Checkout and Log with commands

Resolving Git Branch Merge Conflict

End To End ML Project With Deployment-Github And Code Set Up

Implementing Project Structure, Logging And Exception Handling

Discussing Project Problem Statement,EDA And Model Training

Data Ingestion Implementation

Data Transformation Using Pipelines Implementation

Model Trainer Implementation

Model Hyperparameter Tuning Implementation

Building Prediction Pipeline

ML Project Deployment Using AWS Beanstalk

Deployment EC2 Instance With ECR

Deployment Azure With Container And Images

Project Structure Set up With Environment

Github Repository Set Up With VS Code

Packaging the Project With Setup.py

Logging And Exception Handling Implementation

Introduction To ETL Pipelines

Setting Up MongoDb Atlas

ETL Pipeline Setup With Python

Data Ingestion Architecture

Implementing Data Ingestion Configuration

Implementing Data Ingestions Component

Implementing Data Validation-Part 1

Implementing Data Validation-Part 2

Data Transformation Architecture

Data Transformation Implementation

Model Trainer Implementation- Part 1

Model Trainer And Evaluation With Hyperparameter Tuning

Model Experiment Tracking With MLFLOW

MLFLOW Experiment Tracking With Remote Respository Dagshub

Model Pusher Implementation

Model Training Pipeline Implementation

Batch Prediction Pipeline Implementation

Final Model And Artifacts Pusher To AWS S3 buckets

Building Docker Image And Github Actions

Github Action-Docker Image Push to AWS ECR Repo Implementation

Final Deployment To EC2 instance

Getting Started With MLOPS With MLFlow And Dagshub With Project

Data Versioning Control Implementation

Building Data Science Projects With BentoML

Roadmap to Learn NLP for Machine Learning

Practical Use cases of NLP

Tokenisation and Basic Terminologies

Tokenisation Practicals

Text Preprocessing Stemming using NLTK

Text Preprocessing Lemmatization NLTK

Text Preprocessing Stopwords

Parts of Speech Tagging Using NLTK

Named Entity Recognition

What's Next?

One Hot Encoding Intuition

Advantages and Disadvantages of OHE

Bag of Words Intuition

Advantages and Disadvantages BOW

BOW implementation using NLTK

N Grams

N Gram BOW Implementation Using NLTK

TF-IDF Instituion

Advantages and Disadvantages of TF-IDF

TFIDF Practical implementation Python

Word Embeddings

Word2Vec Intuition

Word2Vec Cbow Intuition

SkipGram Indepth Intuition

Advantages of Word2Vec

AvgWord2vec Indepth Intuition

Word2vec Practical Implementation Gensim

Spam ham Project using BOW

Spam And Ham Project Using TFidf

Best Practises For Solving ML Problems

Part 1-Text Classification With Word2vec And AvgWord2vec

Part 2- Text Classification With Word2vec And AvgWord2vec

Part 1-Kindle Review Sentiment Analysis

Part 2- Kindle Review Sentiment Analysis

Introduction

Why Deep Learning is getting Popular?

3 - Perception Intuition

Advantages and Disadvantages of Perceptron

ANN Intuition and Learning

Back Propogation and Weight Updation

Chain Rule of Derivatives

Vanishing Gradient Problem and Sigmoid

Sigmoid Activation Function

Sigmoid Activation Function 2.0

Tanh Activation Function

Relu activation Function

Leaky Relu and Parametric Relu

ELU Activation Function

Softmax For Multiclass Classification

Which Activation Function To Apply When?

Loss Function Vs Cost Function

Regression Cost Function

Loss Function Classification Problem

Which Loss Function To Use When?

Gradient Descent Optimisers

SGD

Mini Batch With SGD

SGD With Momentum

Adagard

RMSPROP

Adam Optimiser

Exploding Gradient Problem

Weight Initialisation Techniques

Dropout Layers

CNN Introduction

Human Brain Vs CNN

All you need to Know about Images

Convolution Operation In CNN

Padding In CNN

Operation Of CNN Vs ANN

Max, Min and Average Pooling

Flattening and Fully Connected Layers

CNN example with RGB

Discussing Classification Problem Statement And Setting Up Vs Code

Feature Transformation Using Sklearn With ANN

Step By Step Training With ANN With Optimizer and Loss Functions

Prediction With Trained ANN Model

Integrating ANN Model With Streamlit Web APP

Deploying Streamlit web app with ANN Model

ANN Regresiion Practical Implementation

Finding Optimal Hidden Layers And Hidden Neurons In ANN

Introduction To NLP In Deep Learning

Understanding RNN Architecture- RNN Vs ANN

Forward Propogation With Time In RNN Training

Backward Propogation With Time In RNN Training

Problems With RNN

Problem Statement

Getting Started With Word Embedding Layers

Implementing Word Embedding With Keras Tensorflow

Loading And Understanding IMDB Dataset And Feature Engineering

Training Simple RNN With Embedding Layer

Prediction From Trained Simple RNN

End To End Streamlit Web App Integrated With RNN And deployment

Why LSTM RNN?

LSTM RNN Architecture

Forget Gate In LSTM RNN

Input Gate And Candidate Memory In LSTM RNN

Output Gate In LSTM RNN

Training Process In LSTM RNN

Variants Of LSTM RNN

GRU RNN Complete Indepth Intuition

Discussing Problem Statement

Data Collection And Data Processing

LSTM Neural Network Model Training

Prediction From LSTM Model

Streamlit Webapp Integration With LSTM Trained Model

GRU RNN Variant Practical Implementation

Bidirectional RNN Architecture and Intuition

Indepth Intuition Of Encoder And Decoder-Sequence to Sequence Architecture

Problems With Encoder And Decoder

Attention Mechanism Indepth Architecture Explanation

Plan Of Action

What And Why To Use Transformers

Understanding the basic architecture of transformers

Self Attention Layer Working

Multi Head Attention

Feed Forward Neural Network With Multi Head Attention

Positional Encoding Indepth Intuition

Layer Normalization

Layer Normalization Examples

Complete Encoder transformer architecture

Decoder Transformer- Plan Of Action

Decoder Transformer- Masked Multi Head Attention Working

Encoder Decoder Multi Head Attention

Final Decoder Linear And Softmax Layer

NLP Engineer at a News Aggregation Startup

You are a Data Scientist at a Movie Review Platform