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Writing Maintainable, Scalable, and Readable TypeScript Code

Table of Contents Introduction to Code Maintainability Principles of Maintainable TypeScript Code Key Practices for Writing Scalable TypeScript Code Enhancing Readability in TypeScript Code Structuring TypeScript Projects for Scalability Advanced...
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Optimizing Build Times and Incremental Compilation in TypeScript

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Monorepos with TypeScript: Nx, Turborepo Basics

Table of Contents What is a Monorepo? Benefits of Monorepos Overview of Nx and Turborepo What is Nx? What is Turborepo? Setting Up a Monorepo with Nx Setting Up a Monorepo...
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Advanced tsconfig.json: Compiler Flags and Strictness for Large Projects

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Linting and Formatting: ESLint + Prettier for TypeScript

Table of Contents Introduction Why Linting and Formatting Are Critical What is ESLint? What is Prettier? How ESLint and Prettier Work Together Setting Up ESLint in a TypeScript Project Installing Dependencies Configuring...

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Clean Code Principles and Best Practices for TypeScript

Table of Contents Introduction Why Clean Code Matters Core Clean Code Principles Meaningful Names Small, Focused Functions Single Responsibility Principle (SRP) Avoiding Side Effects Favor Composition Over Inheritance DRY (Don’t Repeat Yourself) KISS (Keep...

Event-Driven Programming with Typed Events in TypeScript

Table of Contents Introduction What is Event-Driven Programming (EDP)? Why Typed Events Matter Building a Simple Event System in TypeScript Defining Typed Event Interfaces Creating an Event Emitter Class Subscribing, Emitting,...

Domain-Driven Design (DDD) Basics in TypeScript

Table of Contents Introduction What is Domain-Driven Design (DDD)? Core Concepts of DDD Entities Value Objects Aggregates Repositories Services Structuring a DDD Project in TypeScript Example: Building a Simple DDD Module in TypeScript Best Practices...

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Case Studies and Real-World Projects in Data Science

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From Learning to Doing At this stage, you’ve covered the essential theory, tools, and workflows needed to become a data scientist. The next step is...

Introduction to Model Deployment and MLOps

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Beyond Model Building Building a high-performing machine learning model is only part of the journey. In the real world, models need to be deployed, monitored,...

Introduction to Big Data and Distributed Computing

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Why Big Data? As organizations generate massive volumes of data—from user interactions, IoT sensors, financial transactions, and more—traditional tools like pandas or Excel become insufficient...

Natural Language Processing (NLP) and Text Data

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What is NLP? Natural Language Processing (NLP) is a field at the intersection of computer science, artificial intelligence, and linguistics. It focuses on enabling machines...

Recurrent Neural Networks (RNNs) and Time Series Data

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Introduction to Sequence Modeling Traditional neural networks assume that all inputs and outputs are independent of each other. While this works well for tasks like...

Convolutional Neural Networks (CNNs) for Image Recognition

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Why CNNs? When dealing with image data, traditional neural networks often fall short. Each image pixel becomes a separate input, leading to an explosion in...

Introduction to Neural Networks and Deep Learning

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What is a Neural Network? A neural network is a computational model inspired by the way biological neural networks in the human brain work. It...

Model Evaluation Techniques and Metrics

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Why Evaluate a Model? Once you’ve trained a machine learning model, it’s crucial to assess how well it performs. This step helps you understand if...

Hyperparameter Tuning and Model Optimization

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What Are Hyperparameters? In machine learning, hyperparameters are the external configurations that control the learning process. These parameters are set before training and can significantly...

Introduction to Machine Learning with Scikit-Learn

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What is Machine Learning? Machine learning (ML) is a subset of artificial intelligence (AI) where algorithms learn patterns from data and use them to make...

Data Cleaning and Preprocessing Techniques

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Why Clean Data? Real-world data is rarely in the right shape for analysis. It often contains errors, missing values, and inconsistencies. Data cleaning is a...

Data Visualization with Matplotlib and Seaborn

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Why Visualize Data? No matter how good your analysis is, if others can't understand it, it loses impact. Visualization bridges that gap. Charts help you...
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