Knowledge Base

Artificial Intelligence

Algorithms

Artificial Neural Networks (ANN)

Boltzmann Machines (BM)

Boltzmann Machines (BM)

Deep Boltzmann Machines (DBM)

Restricted Boltzmann Machines (RBM)

Convolutional Neural Networks (CNN)

Convolutional Neural Networks (CNN)

Deconvolutional networks (DN)

Long-Short Term Memory (LSTM)

Gated Recurrent Units (GRU)

Long-Short Term Memory (LSTM)

Neural Turing machines (NTM)

Artificial Neural Networks (ANN)

Autoencoders (AE)

Deep Belief Network (DBN)

FeedForward Neural Networks (FF or FFNN)

Generative Adversarial Networks (GAN)

Graph Convolutional Networks (GCN)

Hopfield Networks (HN)

Radial Basis Function (RBF)

Recurrent Neural Networks (RNN)

Bayesian Models

Naive Bayes

Bernoulli Naive Bayes

Gaussian Naive Bayes

Multinomial Naive Bayes

Averaged One-Dependence Estimators (AODE)

Bayesian Belief Network (BBN)

Bayesian Models

Bayesian Non-Parametrics (BNP)

Ensemble Methods

Random Forest(Random Decision Forest)

AdaBoost (Adaptive Boosting)

Ensemble Methods

Gradient Boosted Regression Trees (GBRT)

Gradient Boosting (GB)

Hierarchical Clustering

Hierarchical Clustering

K-Means

k-Nearest Neighbours (KNN)

k-Nearest Neighbours (KNN)

Regression Models

Decision Tree Regression (DTR)

Gaussian Process Regression

Lasso Regression

Linear Regression

Logistic Regression

Polynomial Regression

Random Forest Regression (RFR)

Ridge Regression

Robust Regression (RANSAC)

Rule-Based Machine Learning (RBML)

Apriori Algorithm

ASSOC Algorithm

Eclat Algorithm

FP-growth Algorithm

Inductive Learning Algorithm (ILA)

OPUS Search Algorithm

Rule-Based Machine Learning (RBML)

Sequential Covering

Support Vector Machine (SVM)

Kernel functions

Support Vector Machine (SVM)

SVM Classification

Tree-based Models

Chi-squared Automatic Interaction Detection (CHAID)

Classification and Regression Tree (CART)

Conditional Decision Trees

Iterative Dichotomiser 3 (ID3)

Tree-based Models

Deep Q Learning (DQN)

Gaussian mixture model (GMM)

Hidden Markov Model (HMM)

Linear Discriminant Analysis (LDA)

Principal Components Analysis (PCA)

Quadratic Discriminant Analysis

Recursive Feature Elimination (RFE)

Applications

Machine Vision

Diffusion Models

Image Generation

Intelligent Document Processing (IDP)

Optical Character Recognition (OCR)

Natural Language Processing (NLP)

Algorithms and Tasks

Bag of Words

Paraphrase Generation

Paraphrase Generation

Question answering

Question answering

Relation prediction

Relation prediction

Relationship extraction

Relationship extraction

Semantic textual similarity

Semantic textual similarity

Sentiment Analysis

Sentiment Analysis

Shallow syntax

Simplification

Stance detection

Stance detection

Summarization

Taxonomy learning

Taxonomy learning

Temporal processing

Temporal processing

Text Classification

Text Classification

Word Embedding Techniques

FastText

Probabilistic FastText

Word2Vec

Neural Probabilistic Model

Co-Occurrence Matrix

Continuous Bag of Words (CBOW)

Continuous Skip-Gram

Embedding Layer

One-Hot Encoding (Word Count Vectorizing)

Poincare Embeddings (Hierarchal Representations)

TF-IDF Transform

Word Embedding Techniques

Algorithms and Tasks

Information Extraction (IE)

Natural Language Generation (NLG)

Natural Language Patterns

Topic Modelling

Applications

Grammar Checkers

Grammatical Error Correction

Machine Translation

Rephrasing - Paraphrasing

Knowledge Systems

Automated Knowledge Base

Commonsense Knowledge Bases

Knowledge base, Knowledge Graph, and Ontologies

Knowledge Fusion

Knowledge Systems

Organizational Data(firmographic or firm demographic)

Linguistics

Lexical Semantics

Phrase Structure Grammar

Natural Language Understanding (NLU)

Intent Recognition

Named Entity Linking (NEL)

Natural Language Inference (NLI)

Natural Language Understanding (NLU)

Semantic Role Labelling (SRL)

NLP Concepts

Inductive Reasoning

Large Language Model (LLM)

Text structure analysis

Ontologies

Ontology Concepts

Attempto Controlled English

Concept-Based Representation

Ontology Learning

Ontology Learning

Pre-Processing

Constituency Parsing

Context-free Grammar(CFG)

Coreference Resolution

Dependency Parsing

Entity Linking (EL)

Named Entity Recognition (NER)

Part-of-speech Tagging (POS)

Positional Encoding

Semantic Parsing

Word Sense Disambiguation

Challenges in NLP

Natural Language Processing (NLP)

Recommender Systems

Collaborative filtering

Content-based filtering System

Evaluating recommender systems

Recommender Systems

Checklists and Processes

Checklists and Processes

Steps in mastering AI

Concepts

Evaluation Metrics

Confusion matrix

Features

Feature Creation

Feature Engineering

Feature Selection

Feature Transformation

Objective function

Cost Function

Stochastic Gradient Descent(SGD)

Loss Functions

Mean Absolute Error Loss(L1 regularization)

Mean Square Error Loss(L2 regularization)

Responsible AI

eXplainable Artificial Intelligence (XAI)

Rule-Based System

Artificial Immune Systems (AIS)

Association Rule Learning

Association Rule Mining

Association Rules

Associative Classifier (AC)

Learning Classifier Systems (LCS)

Rule Extraction

Rule-Based Classification

Rule-Based System

Active Learning

Curriculum Learning

Evaluation Metrics

Knowledge Graphs (KGs)

Markov chains (MC)

Objective function

Optimization Problem

Pattern Recognition

Machine Learning

Machine Learning Concepts

Activation Function

Activation Function

Binary Step Activation Functions

Linear Activation Function

Non-linear Activation Functions

ReLU(Rectified Linear Unit)

Tanh(Hyperbolic Tangent)

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

Neural Architecture Search

Bias and Variance (ML)

Bias and Variance (ML)

Deep learning

Backpropagation

Cross-Validation

Diffusion Models

Discriminative Models

Generative Models

Hyperparameter Tuning

Machine Learning Concepts

Model Evaluation

Model Resource Management

Model Selection

MLOps

Machine Learning Development Lifecycle (MLDLC)

Machine Learning Pipeline

Machine Learning Workflow

Deep Reinforcement Learning (Deep RL)

Machine Learning

Reinforcement Learning

Self-supervised Learning

Semi-supervised Learning

Supervised Machine Learning

Unsupervised Machine Learning

Mathematics of AI

Algebra

Matrices

Matrix Multiplication in Python

Relational algebra

The Hessian Matrix

The Jacobian Matrix

Calculus

Differential Calculus

Integral Calculus

Statistics

Descriptive Statistics

Descriptive Statistics

Probability

Bayesian Statistics

Bayesian Statistics

Markov Chain Monte-Carlo (MCMC)

Variational Inference

Conditional Probability

Statistics Concepts

Bias and Variance(Statistics)

Bias and Variance(Statistics)

Confidence Interval

Continuous Random Variable

Cross-Validation (Statistics)

Discrete Random Variable

Distribution Curves

Hypothesis Testing

Log of the distribution

Monotonic Relationship

Probability Density Function (PDF)

Random Experiment

Random Variables

Standard Deviation

Statistically Significant Effect

Statistics Concepts

Inferential Statistics

Probability Distribution

Mathematics of AI

Regression Mathematics

Tasks & Techniques

Classification

Clustering

Dimensionality Reduction

Dimensionality Reduction

Feature Selection Techniques

Feature Selection Techniques

Regression

Bagging (Technique)

Boosting (Technique)

Regularization (Technique)

Tips & Tricks

Selecting Feature Selection Method

When to use, or not use Machine Learning

AI for Business

Artificial Intelligence

BlockChain

Concepts

Blockchain Architecture

Chain of Blocks

Decentralized Application (DApp)

Distributed Ledger

Zero-Knowledge Proof

Consensus Algorithms

Consensus Algorithms

Delegated Proof-of-Stake (DPoS)

Proof of Work (PoW)

Proof-of-Authority (PoA)

Proof-of-Importance (PoI)

Proof-of-Stake (PoS)

Business & Startups

Business Concepts

Business Concepts

Business Planning Questionnaire

Cash Flow Statement

Cash management & Accounting

Income Statement

Mission Statement

Point of Sale (POS)

Business Skills

Business writing

Startups

Startup Ideas

Types of Startups Ideas

Validating Startup Ideas

Startup Metrics

Startup Metrics

Raising Capital

Startup Failure

Startup Marketing

Startup Mistakes

Startup Survival

Business & Startups

Market Research

Starting a Business - The Process

Cyber Security

Application Security

Secure Software Development Life Cycle(S-SDLC)

Data Flow Diagram

Secure Software Development Life Cycle(S-SDLC)

Source Code Scan

Cryptography

Key & Secret Management

Certificate Management

Encryption Standards

Key & Secret Management

Data Protection

Data Leakage Prevention

Insider Threats

Malware

Trojan (trojan horse)

Network Security

DDOS Prevention

Physical Security

Privacy & Personal Security

Privacy & Personal Security

Self-hosted VPN Server

Risk Assessment

Penetration Test(PenTest)

Dynamic Application Security Testing

Social Engineering

Threat Inteligence

Internal

Indicators of Compromise(IOC)

Training (User Education)

3rd party risk assessment

Risk Monitoring Services

Security Operations(SecOps)

Incident Response

Security Information and Event Management (SEIM)

Security Operations(SecOps)

Security Orchestration, Automation, and Response(SOAR)

Vulnerability Management

Web Security

Web App - Pen Testing Tools

General Laws of Cybersecurity

Penetration Testing(PenTest)

Reconnaissance (Information Gathering)

Security Control

Security Mistakes

Data Science

Data Analysis

Data Analysis Methods

Data Analysis Process

Data Mining

Data Integration

Data Preparation

Data Preparation

Data Transformation

One-Hot Encoding

Data Science Career

Data Science Career

Data Science Career VS Academia

Data Science Skills

Learning Data Science

Data Science Concepts

Data Dictionary

Data Science Concepts

Data Structures

Data Science Lifecycle

Hierarchy of Needs

Hierarchy of Needs

Exploratory Data Analysis (EDA)

Tools and Technologies

Visualization

Data Visualization Libraries

Data Visualization Libraries

Pandas for Data Visualization

Business Analytics

Business Intelligence (BI)

Business Understanding

Data Science Lifecycle

Development

Performance Optimization

Performance Optimization

Python

Cheat Sheet

Development Environment

Conda

Development Environment

pip vs anaconda

Python Virtual Environment

Python Windows Shortcuts

Django

Django Patterns

Django Pagination

HTMX - Forms in Bootstrap

HTMX - Partial page load

Packages

django_components

Ajax & HTMX Compatibility

django_components

django-debug-toolbar

django-extensions

Snippets

upload_to in FileField

Django - Project Shortcuts for Windows

Django Commands

Django Model Managers and Querysets

Django Project Structure

Django Settings

Django Settings Best Practices

Performance Improvements

Setup a Django Project

Module Review

Flet - Flutter apps in python

Snippets

Basic Python

Accessing the elements of the list

Accessing values and keys in dictionary

Case capitalization

Changing elements in a list

Creating a dictionary

Creating a list

Enumerate function

Enumeration class

Filter function

Handling Tuples

List and strings

List Comprehension

Operations on list

Solving counting problems with dictionary

The setdefault() method

Traversing a dictionary

Traversing a list

Python Settings Best Practices

Software Engineering

Objected Oriented Programming(OOP)

SOLID Principles

Software Business Models

Software Engineering Methodologies

Architecture Characteristics

Design Patterns

Engineering Principles

Objected Oriented Programming(OOP)

Software Life Cycle

Task Management

UI UX

Responsive Design

Query Optimization

Software Engineering

Tips, tricks and habits

A blockchain is a digital, decentralized ledger that records transactions on a distributed network so that stored records are immutable and changes require Consensus of the network.

Process of performing a transaction:

Transaction is broadcasted to nodes.
Nodes must reach Consensus by validating the transaction and the user’s status as the owner of the asset.
Each verified transaction is combined with other transactions to create a new “block” of data.
Each newly created block is added to the existing Chain of Blocks.
New changes to chain of blocks is stored across the Blockchain network.

Process of adding a block to Blockchain network:

A node called Miner is will create a new block, containing list of transactions since last block's creation.
The miner provides Proof of Work (PoW) to produce nonce value which is used to create hash.
The miner broadcasts the new block, it's nonce, and hash to the blockchain network for verification.
New block is verified by nodes and is considered mined and is permanently added to the Blockchain network's distributed ledger, and it's recorded transactions are considered to be complete.

Benefits

Decentralized structure making data more resilient to loss, and more democratic
Trust in claim enforced by network rules, cryptographic measures, and Zero-Knowledge Proof.
Security and privacy enforced by cryptography and hashing.
Free from Censorship
Transparency in public transactions.
Traceability by creating an irreversible audit trail.
Reduced costs for specific use-cases.
Improved Speed for specific use-cases.
Digital asset ownership using tokens.
Immutability, ensure by storing hash of transaction in a distributed network.

Drawbacks and Challenges

Higher implementation costs including decentralized network and blockchain system for many use-case.
Lower system performance for many use-cases.
Data modification and high rate of useless data accumulation.

Considerations in Building a Blockchain Network

Purpose and goals of your blockchain
Choosing the right Consensus mechanism
Choosing the right Blockchain Architecture
Implementing the Blockchain System
Deploying the Blockchain System on a distributed network.