Machine Learning Intuition

Course Overview

Install Anaconda and Python 3 on Ubuntu Machine

Install Anaconda and Python 3 on Windows 10

Install VS Code

Jupyter Notebook Shortcuts

Install Git Bash and Commander Terminal

Install Anaconda and Python 3 on Mac Machine

Python Data Types Part 2

Python Data Types Part 1

Mutable and Immutable Data Types

Python Data Types Conversion

Working with String Methods

String Formatting

Working with List Part 1

String Assignment

Working with Set Part 1

Working with List Part 2

Working with Tuple

Working with Set Part 2

Working with Truthy and Falsy Condition

Working with Boolean and Logical Operators

Working with Dictionary

If Else If Conditional Statement Part 1

If Else If Conditional Statement Part 2

Working with continue and break statements in Loops

Working with for and while() Loops

Method and Lambda Function Part 1

Working with range iterators

Exception (Error) Handling

Method and Lambda Function Part 2

Comprehensions Methods

Working with Dates and Times

Create Your Own Python Module

How to Create Numpy 1D, 2D and 3D Array

Create Array using Ones and Zeros in Numpy

Statistical Operations in Numpy

Working with Inf and NaN in Numpy

All About Shape, Reshape, Ravel, Flatten in Numpy

All About the Sequence and Repetitions in Numpy

Random Numbers in Numpy

How to Index 1D, 2D, and 3D Numpy Array

Importance of Where(), ArgMax(), ArgMin() in ML Models

Save Preprocessed Arrays with File Read and Write

Concatenate and Sorting

Working with Dates in Numpy

Selecting Subset of Columns and Doing Arithmetic Operations on Columns

Pandas File Reading from Local and Online

Write File with Custom Column Separator

Using Lambda Function with Pandas Dataframe

Dataframe Slicing

Head, Tail, Sample, Frac and Random State in Pandas

Column Renaming and Selection Based on Data Types

Getting Information About Dataframe with Info, Shape, Duplicated, and Drop

Data Imputation with Pandas Dataframe

Dataframe Filtering Based on Condition on Columns

Handling NaN and Null Values in Dataframe

Lambda Function for Feature Engineering Part 1

Importance of Groupby and Aggregation in Smart Data Imputation

Multi Columns Grouping and Aggregation

Pandas Inner Merging

Pandas Left, Right, Outer and Concat Joining

Handling Categorical Data

Sorting Pandas Dataframe

Handling Dates with Pandas

Create Your First File in write Mode

Read Your First File

Many Ways to Write Multiple Lines

How to Write List in File and Evaluate It in Read Mode

ReadWrite Multisheet Excel File

ReadWrite json Data with Pandas

Reading CSV and TSV Files

Read Large Files in Chunks

How to Read Nested json Data in Dataframe

Read Audio from Local File and Convert into Text

Read Audio from Microphone to Convert it into Text Data

Covert PDF data into Text Data for ML Models

Introduction

Matching End of String with $ and use of Other Metacharacters

Testing Start of Character Set with ^ (Caret) Metacharacter

Quantifiers Match with Regex101

Matching Specific Set of Characters like 3D or A4

Excluding Specific Set of Characters

Searching for a Pattern with re.search() in Python

Using Escape Chars for Quick Match and Use Regex101 to Find Prebuilt Regex

Matching a Pattern with re.match() in Python

Finding All Matches with re.findall() in Python

Splitting a String with re.split() in Python

Replacing Matches with re.sub() in Python

Introduction to Spacy

Spacy Tokenization Part 2

Spacy Tokenization Part 1

POS Tagging

Dependency Parsing Part 1

Lemmatization (Convert Tokens into Base Form)

Dependency Parsing Part 2

Vector Similarity Introduction

Named Entity Recognition (NER) with Pre-Built Model

Measure Cosine Similarity Between Words

NLTK Tokenization with PUNKT Model

Stemming

Filtering Stop Words with BERT Text Data

POS Tagging with NLTK

Lemmatization with wordnet in NLTK

Finding Collocations - Finding Words Occurring Together

Chunking Noun Phrases

Using Named Entity Recognition (NER) with NLTK

Tweet Characters Count

Tweets Data Loader

Stop Words Count

Word Counts and Average Word Length

Count #HashTags and @Mentions

Preprocessing and Cleaning - Lower Case Conversion

UPPER case words count

Count numeric digits present in tweets

Expand Contracted Form of Words

Remove RT (Retweet) from Tweets

Extract, Count and Remove URLs

Extract, Count and Remove Emails

Remove Accented Chars

Remove Repeated Characters

Remove HTML tags

Remove Mentions, Special Chars and Punctuation

Remove Stop Words

Rare Words Removal

Common Words Removal

Convert into base or root form of word

Word Cloud Visualization

N-Gram and Word Cloud

Spelling Correction

Extract Noun Phrases Like Google Map Reviews

Word Counts, Singularize, Pluralize, Lemmatize and so much more

Language Translation and Detection

Use TextBlob's Inbuilt Sentiment Classifier

Package Files and Directory Setup

Why Setup.py is Needed

Readme.md and License Preparation

Complete Package Setup

Put Your First Method Inside Python Package

Putting General Feature Extraction in Your Python Package

Prepare Empty Python Package and Do Testing

Putting Text Preprocessing Codes Together Part 1

Putting Text Preprocessing Codes Together Part 2

Putting Text Preprocessing Codes Together Part 3

Testing Our Python Package Locally - It Worked

Importance of Uploading Package to GitHub and PyPi. Install Git for Windows

Upload Package to GitHub

Create and Add SSH Key to GitHub Account

Install Your Package from GitHub and Share Install Instruction with Anyone

Adding Package Documentation, Use Cases and One Shot Cleaning

Create PyPi Account to Upload Your Package

Testing Your Python Package with GitHub Installation Method

Upload Your Package to PyPi (Pip) Server for Open Source Use

Why Machine Learning Algorithms

Types of Machine Learning Systems

What is Linear Regression

Evaluation Metrics for Regression

Load California Housing Dataset

Linear Regression Cost Function

Linear Regression Coding on Housing Dataset

Logistic Regression and Related Interview Questions on Log Odds and Logits

Logistic Regression Cost Function - Log Loss and Entropy Discussions

Interview Question - Is Accuracy Good Metric to Measure Model Performance

Logistic Regression vs Linear Regression Discussions for Job Interviews

Logistic Regression Coding for Breast Cancer Classification

Load Breast Cancer Dataset

Explain Confusion Matrix, Accuracy, Precision, Recall, F1-Score to Interviewer

Complete Your ROC-AUC and Precision-Recall Curve Coding

Explain Roc-Auc and Precision-Recall Curve to Your Interviewer

Calculate Precision, Recall and F1-Score in Classification Report by Yourself

Fundamental Understanding of Model Regularization

Why L1 Regularization Produces Sparse Solution but not L2

Regularization Coding for Classification Model

What is Support Vector Machine (SVM) and Hinge Loss

SVM Coding with Regularization

KNN Coding

What is KNN and Its Cost Function

How Decision Tree Works

Decision Tree Coding

Calculate Gini Impurity and Entropy By Hand with An Example

Deep Dive in Decision Tree Parameters which Controls Overfitting

Reduce Decision Tree Overfitting with Regularization

Visualize Decision Tree Pruning Process

How Random Forest Works

Training Random Forest in Regularized Mode

What is Cross Validation

Hyperparameter Tuning Introduction

K-Fold Cross Validation

Leave-One-Out Cross Validation (LOOCV) Coding

GridSearchCV Parameters Preparations

Finding Best Parameters with GridSearchCV Coding

RandomizedSearchCV for Faster Hyper-Parameter Tuning

Text Feature Extraction Intuition Part 1

Bag of Words (BoW) Code Along in Python

Term Frequency (TF) Code Along in Python

Inverse Document Frequency (IDF) Code Along in Python

Text Feature Extraction Intuition Part 2

TFIDF Code Along in Python

Load Spam Dataset

Balance Dataset

Exploratory Data Analysis (EDA)

Data Preparation for Training

Test Your Model with Real Data

Build and Train SVM and Random Forest Models

How Sentiment is Detected from Text Data

Text Preprocessing Package Install

Data Preparation for Model Training

Text Cleaning and Preprocessing

ML Model Building and Training

Logistic Regression Model Evaluation

Load and Store ML Model

Traning and Hyperparameters Tuning of SVM

Install Flask

Run Flask Server

Model Preparation with Flask

Running Flask App with ML Model Part 1

Running Flask App with ML Model Part 2

Getting Familiar with Data

What is Multi-Label Classification

Loading Dataset

Multi-Label Binarization

Text to TFIDF Vectors

Improving and Saving the Model

Model Building and Jaccard Score

What is word2vec

How to Get word2vec

Word Vectors with Spacy

Data Preparation

Semantic Similarity with Spacy

Data Preprocessing

Get word2vec from DataFrame

Split Dataset in Train and Test

ML Model Traning and Testing

Support Vector Machine on word2vec

Test Every Machine Learning Model

Grid Search Cross Validation for Hyperparameters Tuning

What is GloVe Vectors Part 2

What is GloVe Vectors Part 1

Data Preparation

Preprocessing and Cleaning of Emotion Text Data

Download Pre-trained GloVe Vectors

Load GloVe Vector

Text to GloVe on Pandas DataFrame

Text to GloVe Vectors

ML Model Training and Testing

Support Vector Machine for Emotion Recognition

Predict Text Emotion with Custom Data

Resume (CV) Parsing Introduction

NER Training Data Preparation

NER Training Introduction and Config Setup

Training Configuration File Explanation

NER Training Data Preparation Part 2

NER Training Data Preparation Part 1

NER Training with Transformers

CV Parsing and NER Prediction

What Makes Deep Learning State-of-the-Art

What is Deep Learning

How Deep Learning Works

How Deep Learning Learns

Types of Neural Networks in Deep Learning - ANN

What is the Difference Between Deep Learning and Machine Learning

Types of Neural Networks in Deep Learning - CNN

Get the word2vec

Build ANN - Steps for Building Your First Model

Python Package Installation

Data Preprocessing

Feature Standardization

Train Test and Split

Confusion Matrix Plot

ANN Model Building and Training

Setting Custom Threshold

Plot Learning Curve

Model Load, Store and Testing

D CNN Model Building and Training

Import Python Package

Text Preprocessing

Dataset Balancing

Hate Speech Classification Introduction

Train Test and Split

Text Tokenization

Build and Train CNN

Model Testing

Load Store Model

Testing with Custom Data

Introduction to Reccurent Neural Network (RNN)

Types of RNN

The Problem of RNN's or Long-Term Dependencies

Long Short Term Memory (LSTM) Networks

Sequence Generation Scheme

Loading Poetry Dataset

Prepare Training Data

Tokenization

Padding

LSTM Model Training

Poetry Generation Part 1

Poetry Generation Part 2

Download Dataset

Disaster Tweets Dataset Understanding

Target Class Distribution

Number of Characters Distribution in Tweets

One-Shot Data Cleaning

Number of Words, Average Words Length, and Stop words Distribution in Tweets

Most and Least Common Words

Disaster Words Visualization with Word Cloud

Classification with TF-IDF and SVM

Classification with Word2Vec and SVM

Word Embeddings and Classification with Deep Learning Part 1

Word Embeddings and Classification with Deep Learning Part 2