~ Tutorials, reflections, and everything in between ~
~ Tutorials, reflections, and everything in between ~
🧩 Part 5/15
✔ What is Kafka Streams and Why Use It?
✔ How to Install and Set Up Kafka Streams with Python
✔ How to Create and Consume Data Streams with Kafka Streams
✔ How to Apply Operators and Transformations on Data Streams
✔ Filtering and Mapping
✔ Aggregating and Reducing
✔ Joining and Merging
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🧩 Part 4/15
✔ Common Errors and Exceptions in Kafka and Python
✔ Broker Errors
✔ Producer Errors
✔ Consumer Errors
✔ How to Handle Errors and Exceptions in Kafka and Python
✔ Using Try-Except Blocks
✔ Using Error Callbacks
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🧩 Part 3/10
✔ Data Sources for Question Answering
✔ Web Scraping and APIs
✔ Pre-existing QA Datasets
✔ Data Preprocessing Techniques
✔ Text Cleaning and Tokenization
✔ Stop Word Removal and Lemmatization
✔ Building a QA Corpus
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🧩 Part 2/10
✔ Types of Questions
✔ Closed-Ended Questions
✔ Open-Ended Questions
✔ Hypothetical Questions
✔ Types of Answers
✔ Direct Answers
✔ Indirect Answers
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🧩 Part 1/10
✔ What Is Question Answering?
✔ The Importance of Question Answering in NLP
✔ How Does Question Answering Work?
✔ Common Challenges in Question Answering
✔ Types of Question Answering Models
✔ Retrieval-Based QA
✔ Generative QA
✔ Evaluation Metrics for QA Systems
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🧩 Part 3/10
✔ What is FastAPI?
✔ What is Data Validation?
✔ How to Validate Data with FastAPI
✔ Define a Pydantic Model
✔ Declare a Path Operation with a Model
✔ Test the Validation
✔ What is OpenAPI Schema?
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🧩 Part 2/10
✔ What are Path Parameters?
✔ How to Define Path Parameters in FastAPI
✔ How to Validate Path Parameters with Pydantic Models
✔ What are Query Parameters?
✔ How to Define Query Parameters in FastAPI
✔ How to Validate Query Parameters with Pydantic Models
✔ What are Request Body Parameters?
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🧩 Part 1/10
✔ Setting up the Environment
✔ Installing Python and Pip
✔ Installing FastAPI and Uvicorn
✔ Creating a Hello World Endpoint
✔ Writing the Code
✔ Running the Server
✔ Testing the Endpoint
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🧩 Part 6/8
✔ Transformer Architecture and BERT
✔ Transformer Encoder and Decoder
✔ BERT and Masked Language Modeling
✔ XLNet and Permutation Language Modeling
✔ Permutation Language Modeling and Autoencoding
✔ Two-Stream Attention and Autoregressive Modeling
✔ Comparison and Applications of XLNet and BERT
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🧩 Part 5/8
✔ Transformer-XL Architecture
✔ Recurrence Mechanism
✔ Relative Positional Encoding
✔ Transformer-XL Applications
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🧩 Part 4/8
✔ What is Text-to-Text Transfer Learning?
✔ What is T5 and How Does It Work?
✔ The T5 Model Architecture
✔ The T5 Pre-training and Fine-tuning Objectives
✔ How to Use T5 for Various NLP Tasks?
✔ Text Summarization
✔ Text Generation
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🧩 Part 6/12
✔ What are Mean Absolute Error and Mean Absolute Percentage Error?
✔ Mean Absolute Error (MAE)
✔ Mean Absolute Percentage Error (MAPE)
✔ How to Calculate Mean Absolute Error and Mean Absolute Percentage Error in Python?
✔ How to Interpret Mean Absolute Error and Mean Absolute Percentage Error?
✔ Advantages and Disadvantages of MAE and MAPE
✔ How to Compare MAE and MAPE with Other Metrics?
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🧩 Part 5/12
✔ What is Mean Squared Error?
✔ How to Calculate Mean Squared Error
✔ How to Interpret Mean Squared Error
✔ What is R-Squared?
✔ How to Calculate R-Squared
✔ How to Interpret R-Squared
✔ How to Compare Mean Squared Error and R-Squared
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🧩 Part 4/12
✔ What is ROC Curve and AUC?
✔ ROC Curve for Binary Classification
✔ AUC for Binary Classification
✔ ROC Curve and AUC for Multi-class Classification
✔ How to Plot ROC Curve and AUC in Python?
✔ Load and Prepare the Data
✔ Train and Test Different Classifiers
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🧩 Part 3/12
✔ What is Uncertainty and Why is it Important?
✔ Types of Uncertainty
✔ Sources of Uncertainty
✔ Uncertainty Metrics
✔ Confidence Intervals
✔ Entropy and Information Gain
✔ Bayesian Model Evidence
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🧩 Part 2/12
✔ What is Uncertainty in Machine Learning?
✔ Aleatoric Uncertainty
✔ Epistemic Uncertainty
✔ How to Measure and Quantify Uncertainty?
✔ How to Reduce and Mitigate Uncertainty?
✔ Applications and Benefits of Uncertainty Estimation
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🧩 Part 1/12
✔ What is Uncertainty in Machine Learning?
✔ Why is Uncertainty Important for Machine Learning?
✔ Uncertainty for Model Evaluation
✔ Uncertainty for Decision Making
✔ How to Quantify and Estimate Uncertainty in Machine Learning?
✔ Uncertainty in Supervised Learning
✔ Uncertainty in Unsupervised Learning
✔ Uncertainty in Reinforcement Learning
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🧩 Part 6/10
✔ What are Transactions and Why are They Important?
✔ Factors Affecting Transaction Performance and Scalability
✔ Transaction Size
✔ Transaction Isolation Level
✔ Transaction Concurrency
✔ Transaction Locking and Deadlocks
✔ How to Optimize Transaction Performance and Scalability
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🧩 Part 5/10
✔ What are Deadlocks and How Do They Occur?
✔ The Concept of Locking
✔ The Conditions for Deadlock Formation
✔ How to Detect and Resolve Deadlocks
✔ Deadlock Detection Algorithms
✔ Deadlock Resolution Strategies
✔ How to Prevent Deadlocks
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🧩 Part 4/10
✔ What are Transaction Isolation Levels?
✔ READ UNCOMMITTED
✔ READ COMMITTED
✔ REPEATABLE READ
✔ SERIALIZABLE
✔ How to Choose the Right Transaction Isolation Level?
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🧩 Part 3/10
✔ What are Intents and Entities?
✔ Intents
✔ Entities
✔ How to Create and Manage Intents and Entities in Dialogflow
✔ Creating Intents
✔ Adding Training Phrases
✔ Defining Parameters
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🧩 Part 2/10
✔ What is Dialogflow?
✔ How to create a Dialogflow agent
✔ How to add intents and entities to your agent
✔ How to test your agent using the simulator
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🧩 Part 1/10
✔ What is Dialogflow?
✔ How Dialogflow works
✔ Agents
✔ Intents
✔ Entities
✔ Fulfillment
✔ Setting up Dialogflow
✔ Creating an account
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🧩 Part 3/8
✔ What is GPT-3 and how does it work?
✔ The architecture of GPT-3
✔ The training data and parameters of GPT-3
✔ What are the main features and capabilities of GPT-3?
✔ Text generation
✔ Zero-shot and few-shot learning
✔ Language modeling and natural language understanding
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🧩 Part 2/8
✔ What is BERT?
✔ Pre-training BERT
✔ Fine-tuning BERT
✔ BERT Variants and Applications
✔ RoBERTa
✔ ALBERT
✔ DistilBERT
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🧩 Part 3/15
✔ What are Linked Lists?
✔ Singly Linked Lists
✔ Doubly Linked Lists
✔ Circular Linked Lists
✔ What are Stacks?
✔ Stack Operations
✔ Stack Implementation using Arrays
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🧩 Part 2/15
✔ Arrays in Java
✔ What is an array?
✔ How to declare and initialize an array?
✔ How to access and modify array elements?
✔ Advantages and disadvantages of arrays
✔ ArrayLists in Java
✔ What is an arraylist?
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🧩 Part 1/15
✔ What are Data Structures and Algorithms?
✔ Types of Data Structures and Algorithms
✔ Linear Data Structures
✔ Non-linear Data Structures
✔ Sorting Algorithms
✔ Searching Algorithms
✔ How to Choose the Right Data Structure and Algorithm for a Problem?
✔ How to Measure the Complexity and Efficiency of Data Structures and Algorithms?
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🧩 Part 1/8
✔ What is Natural Language Processing (NLP)?
✔ What are the Challenges of NLP?
✔ Ambiguity
✔ Diversity
✔ Complexity
✔ What are the Traditional Approaches to NLP?
✔ Rule-Based Methods
✔ Statistical Methods
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🧩 Part 3/8
✔ Installing and Importing BeautifulSoup4
✔ Parsing HTML Documents with BeautifulSoup4
✔ Searching HTML Elements by Name
✔ Searching HTML Elements by Attributes
✔ Searching HTML Elements by Text
✔ Searching HTML Elements by CSS Selectors
✔ Using Filters to Refine Search Results
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🧩 Part 2/8
✔ What is BeautifulSoup4?
✔ How to Install BeautifulSoup4
✔ How to Parse HTML with BeautifulSoup4
✔ How to Navigate the HTML Tree with BeautifulSoup4 Methods
✔ find() and find_all()
✔ select() and select_one()
✔ get_text() and strings
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🧩 Part 1/8
✔ What is Web Scraping?
✔ Why Web Scraping is Useful?
✔ How to Install BeautifulSoup4 in Python?
✔ How to Parse HTML with BeautifulSoup4?
✔ How to Extract Data from HTML Elements?
✔ How to Handle Exceptions and Errors?
✔ How to Save and Export the Scraped Data?
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🧩 Part 3/12
✔ What is Object-Oriented Programming?
✔ Java Classes and Objects
✔ Creating and Using Classes
✔ Constructors and Methods
✔ Access Modifiers and Encapsulation
✔ Java Inheritance and Polymorphism
✔ Extending Classes and Overriding Methods
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🧩 Part 2/12
✔ What are Control Statements in Java?
✔ Types of Control Statements in Java
✔ Selection Statements
✔ Iteration Statements
✔ Jump Statements
✔ Java Conditionals: if-else and switch-case
✔ The if-else Statement
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🧩 Part 1/12
✔ What are Variables in Java?
✔ Declaring and Initializing Variables
✔ Variable Naming Conventions
✔ What are Data Types in Java?
✔ Primitive Data Types
✔ Reference Data Types
✔ What are Operators in Java?
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🧩 Part 6/15
✔ What is Flask-Login?
✔ Setting up the Project
✔ Creating the User Model
✔ Password Hashing and Verification
✔ User Registration and Login Forms
✔ User Authentication and Session Management
✔ User Authorization and Access Control
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🧩 Part 5/15
✔ Setting Up the Project
✔ Creating the Database Model
✔ Configuring the Database URI
✔ Initializing the Database
✔ Performing CRUD Operations
✔ Querying the Database
✔ Updating and Deleting Data
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🧩 Part 4/15
✔ Installing and Configuring Flask-WTF
✔ Creating and Rendering Forms
✔ Validating and Processing Form Data
✔ Adding CSRF Protection to Your Forms
✔ Customizing Your Forms with Templates and Widgets
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🧩 Part 6/8
✔ Prerequisites
✔ Connecting to MongoDB
✔ Updating a Single Document
✔ Updating Multiple Documents
✔ Using Update Operators
✔ Handling Update Errors
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🧩 Part 5/8
✔ Setting Up the MongoDB Java Driver
✔ Connecting to a MongoDB Database
✔ Querying Documents from a MongoDB Collection
✔ Using the find Method
✔ Using Filters to Specify Query Criteria
✔ Using Projections to Specify Fields to Return
✔ Using Sorts to Order the Query Results
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🧩 Part 4/8
✔ Setting Up the MongoDB Java Driver
✔ Creating a MongoDB Collection
✔ Inserting a Single Document into a MongoDB Collection
✔ Inserting Multiple Documents into a MongoDB Collection
✔ Inserting Documents with Different Data Types into a MongoDB Collection
✔ Inserting Documents with Embedded Documents and Arrays into a MongoDB Collection
✔ Inserting Documents with Filters and Options into a MongoDB Collection
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🧩 Part 3/5
✔ Creating a Sample Table
✔ Inserting Data into a Table
✔ Updating Data in a Table
✔ Deleting Data from a Table
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🧩 Part 2/5
✔ PostgreSQL SELECT Statement Syntax
✔ SELECT Clause
✔ FROM Clause
✔ WHERE Clause
✔ ORDER BY Clause
✔ PostgreSQL SELECT Statement Examples
✔ Selecting All Columns from a Table
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🧩 Part 1/5
✔ PostgreSQL CREATE TABLE Syntax
✔ Basic Syntax
✔ Column Definition
✔ Table Constraints
✔ PostgreSQL Data Types
✔ Numeric Data Types
✔ Character Data Types
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🧩 Part 3/15
✔ What is Kafka and Why Use It?
✔ Kafka Concepts: Topics, Partitions, and Offsets
✔ Setting Up the Environment
✔ Creating Kafka Topics with Python
✔ Deleting Kafka Topics with Python
✔ Listing Kafka Topics with Python
✔ Working with Partitions and Offsets with Python
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🧩 Part 2/15
✔ What is Kafka and Why Use It?
✔ Setting Up Kafka and Python
✔ Producing Messages with Kafka and Python
✔ Creating a Kafka Producer
✔ Sending Messages to a Kafka Topic
✔ Configuring the Kafka Producer
✔ Serializing Messages with JSON and Avro
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🧩 Part 1/15
✔ What is Kafka and Why Use It?
✔ How to Install Kafka on Windows, Mac, or Linux
✔ Download and Extract Kafka Binaries
✔ Start ZooKeeper and Kafka Server
✔ Create and Test a Kafka Topic
✔ How to Install Python and Pip on Windows, Mac, or Linux
✔ How to Install and Use Kafka-Python Library
✔ How to Produce and Consume Messages with Python and Kafka
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🧩 Part 3/10
✔ Data Ingestion in Elasticsearch
✔ Ingest Nodes and Plugins
✔ Ingest APIs and Methods
✔ Data Preprocessing in Elasticsearch
✔ Pipelines and Processors
✔ Transforms and Aggregations
...
🧩 Part 2/10
✔ What is Elasticsearch?
✔ How to Install and Run Elasticsearch
✔ Basic Concepts of Elasticsearch
✔ Documents and Indices
✔ CRUD Operations
✔ Search Operations
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🧩 Part 1/10
✔ What is Elasticsearch and why use it for ML?
✔ Elasticsearch architecture and components
✔ Nodes and clusters
✔ Indices and shards
✔ Documents and mappings
✔ How to install Elasticsearch on Windows, Linux, and Mac
✔ How to verify and test your Elasticsearch installation
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🧩 Part 9/10
✔ What are Large Language Models and How are They Fine-Tuned?
✔ Ethical and Social Implications of Fine-Tuning Large Language Models
✔ Bias and Fairness
✔ Privacy and Security
✔ Accountability and Transparency
✔ Responsible AI: Best Practices and Guidelines for Fine-Tuning Large Language Models
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🧩 Part 8/10
✔ Deployment Options
✔ Cloud Platforms
✔ Containers
✔ APIs
✔ Serving Strategies
✔ Batch Inference
✔ Online Inference
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🧩 Part 3/15
✔ What are Templates and Static Files?
✔ Templates
✔ Static Files
✔ How to Create and Use Templates in Flask
✔ How to Create and Use Static Files in Flask
✔ How to Customize Your Templates with Jinja2
✔ How to Add Interactivity with JavaScript
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🧩 Part 3/8
✔ Setting Up MongoDB and Java Environment
✔ Connecting to MongoDB Database
✔ Creating MongoDB Collections using Java
✔ Using createCollection Method
✔ Using MongoCollection Interface
✔ Dropping MongoDB Collections using Java
✔ Using drop Method
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🧩 Part 2/8
✔ Prerequisites
✔ Installing MongoDB Driver for Java
✔ Creating a MongoClient Object
✔ Connecting to a MongoDB Server
✔ Creating a MongoDatabase Object
✔ Performing CRUD Operations
✔ Closing the Connection
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🧩 Part 1/8
✔ MongoDB Installation
✔ Download MongoDB
✔ Install MongoDB
✔ Run MongoDB
✔ Java Installation
✔ Download Java
✔ Install Java
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🧩 Part 3/10
✔ What are Errors and Exceptions in Transactions?
✔ Types of Errors and Exceptions
✔ Effects of Errors and Exceptions on Transactions
✔ How to Use Try-Catch Blocks to Handle Errors and Exceptions
✔ Syntax and Examples of Try-Catch Blocks
✔ Benefits and Limitations of Try-Catch Blocks
✔ How to Use Savepoints to Handle Errors and Exceptions
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🧩 Part 2/10
✔ What are Transactions and Why are They Important?
✔ How to Start a Transaction in SQL
✔ How to Commit a Transaction in SQL
✔ How to Rollback a Transaction in SQL
✔ How to Handle Errors and Exceptions in Transactions
✔ How to Use Savepoints in Transactions
✔ How to Set Transaction Isolation Levels in SQL
✔ How to Optimize Transaction Performance in SQL
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🧩 Part 1/10
✔ What is a Database Transaction?
✔ What are the ACID Properties of Database Transactions?
✔ Atomicity
✔ Consistency
✔ Isolation
✔ Durability
✔ What is Concurrency Control and Why is it Needed?
✔ How to Implement Database Transactions in SQL?
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🧩 Part 2/15
✔ What is Flask and Why Use It?
✔ Flask Features
✔ Flask vs Other Frameworks
✔ Setting Up the Environment
✔ Creating a Flask App
✔ Routing and Views
✔ Displaying a Hello World Message
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🧩 Part 1/15
✔ Installing Python
✔ Creating a Virtual Environment
✔ What is a Virtual Environment?
✔ How to Create and Activate a Virtual Environment?
✔ Installing Packages with pip
✔ What is pip?
✔ How to Install and Upgrade Packages with pip?
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🧩 Part 3/12
✔ What is Confusion Matrix?
✔ How to Calculate Confusion Matrix?
✔ How to Interpret Confusion Matrix?
✔ How to Calculate Accuracy, Precision, Recall, and F1-score from Confusion Matrix?
✔ How to Use Confusion Matrix for Model Selection and Improvement?
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🧩 Part 2/12
✔ What is an Evaluation Metric?
✔ Types of Evaluation Metrics
✔ Classification Metrics
✔ Regression Metrics
✔ Clustering Metrics
✔ How to Choose the Right Evaluation Metric
✔ Understand the Problem and the Data
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🧩 Part 1/12
✔ What is Machine Learning Evaluation?
✔ Why is Machine Learning Evaluation Important?
✔ To Measure the Performance of a Model
✔ To Compare Different Models
✔ To Identify the Strengths and Weaknesses of a Model
✔ What are the Types of Machine Learning Evaluation?
✔ Supervised Learning Evaluation
✔ Unsupervised Learning Evaluation
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🧩 Part 7/10
✔ Fine-Tuning Large Language Models: Challenges and Opportunities
✔ Challenges of Fine-Tuning Large Language Models
✔ Opportunities for Improving Performance and Efficiency
✔ Pruning: Reducing the Number of Parameters
✔ Pruning Methods and Techniques
✔ Pruning Results and Trade-offs
✔ Quantization: Reducing the Precision of Parameters
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🧩 Part 6/10
✔ Memory Errors
✔ Reducing Batch Size
✔ Using Gradient Checkpointing
✔ Using Mixed Precision Training
✔ Gradient Explosion
✔ Clipping Gradients
✔ Using Gradient Accumulation
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🧩 Part 5/10
✔ Fine-Tuning Large Language Models
✔ What is Fine-Tuning?
✔ Why Fine-Tune Large Language Models?
✔ How to Fine-Tune Large Language Models?
✔ Loss Functions for Fine-Tuning
✔ Cross-Entropy Loss
✔ Contrastive Loss
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🧩 Part 4/10
✔ Choosing a Framework: PyTorch vs TensorFlow
✔ Installing Libraries and Dependencies
✔ Loading Pre-trained Models
✔ Configuring Hyperparameters
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🧩 Part 3/10
✔ What are Large Language Models?
✔ How to Choose a Model for Fine-Tuning?
✔ Model Size and Architecture
✔ Model Availability and Accessibility
✔ Model Performance and Generalization
✔ How to Choose a Task for Fine-Tuning?
✔ Task Type and Complexity
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🧩 Part 2/10
✔ Data Preparation
✔ Data Cleaning and Filtering
✔ Data Augmentation and Sampling
✔ Preprocessing
✔ Tokenization
✔ Masking
✔ Batching
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🧩 Part 1/10
✔ What are Large Language Models?
✔ Why are Large Language Models Important?
✔ How to Fine-Tune Large Language Models?
✔ Data Preparation
✔ Model Selection
✔ Hyperparameter Tuning
✔ Evaluation and Deployment
✔ Examples of Fine-Tuning Large Language Models
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