Core Concepts

C# .NET Core Basics Cheat Sheet

Introduces ASP.NET Core and .NET fundamentals: Program.cs setup, dependency injection lifetimes, configuration, and the dotnet CLI workflow.

Apache Spark (PySpark) Cheat Sheet

PySpark reference covering SparkSession setup, DataFrame transformations and actions, Spark SQL queries, caching, and writing partitioned output.

Dask Cheat Sheet

Dask reference covering parallel DataFrame and Array APIs, delayed task graphs, lazy evaluation, and the distributed scheduler client.

Weights & Biases Cheat Sheet

A guide to Weights & Biases for experiment tracking, hyperparameter sweeps, artifact versioning, and logging metrics and media during model training.

Airflow Cheat Sheet

A cheat sheet for Apache Airflow covering DAG authoring with the TaskFlow API, operators, task dependencies, and essential CLI commands.

Reinforcement Learning Basics Cheat Sheet

A quick reference to core RL concepts, algorithms like Q-learning and policy gradients, and how to implement a simple agent with OpenAI Gym/Gymnasium.

MLOps Fundamentals Cheat Sheet

Summarizes MLOps practices for experiment tracking, model versioning, and continuous training pipelines using tools like MLflow, DVC, and CI/CD automation.

Tableau Basics Cheat Sheet

Introduces Tableau's dimensions, measures, calculated fields, and Level of Detail expressions for building interactive dashboards and worksheets.

Power BI Basics Cheat Sheet

Covers Power BI's data model, DAX measures, star schema design, and common visuals for building interactive business intelligence reports.

Data Warehousing Concepts Cheat Sheet

Covers dimensional modeling, star vs. snowflake schemas, ETL/ELT pipelines, OLAP operations, and slowly changing dimensions for building analytical data wareho…

Survival Analysis Cheat Sheet

Covers censoring, the survival and hazard functions, Kaplan-Meier estimation, and Cox proportional hazards regression using the lifelines library.

Markov Chains Cheat Sheet

Explains states, transition matrices, and the Markov property, and shows how to simulate chains and compute stationary distributions in Python.

Monte Carlo Simulation Cheat Sheet

Covers the core idea of Monte Carlo estimation, random sampling, and variance reduction, with Python examples for integration and probability estimation.

Batch Normalization Cheat Sheet

Explains why batch normalization stabilizes training, its learnable scale and shift parameters, and how train versus eval mode statistics differ in PyTorch.

Transfer Learning Cheat Sheet

Covers feature extraction versus fine-tuning, freezing layers, and practical PyTorch code for adapting a pretrained model to a new task.

Generative Adversarial Networks (GANs) Cheat Sheet

Explains the generator-discriminator minimax game, common failure modes like mode collapse, and a minimal PyTorch training loop for a GAN.

Diffusion Models Cheat Sheet

Covers the forward noising process, learned reverse denoising process, and practical text-to-image inference with the Hugging Face diffusers library.

LLM Fine-Tuning Basics Cheat Sheet

Covers full fine-tuning versus parameter-efficient methods like LoRA and QLoRA, and shows how to configure PEFT for fine-tuning with Hugging Face.

Vector Databases for AI Cheat Sheet

Explains embeddings, approximate nearest neighbor search, and indexing strategies like HNSW, with code for storing and querying vectors using common libraries.

Svelte Cheat Sheet

A concise guide to Svelte 5 runes, reactive state, template syntax, and stores for building fast, compiler-driven components.

Redux Cheat Sheet

A reference for Redux Toolkit's store setup, slices, reducers, and React bindings for predictable, centralized state management.

React Query (TanStack Query) Cheat Sheet

A reference for TanStack Query's useQuery and useMutation hooks, cache keys, and invalidation strategies for server-state management.

Remix Cheat Sheet

A reference for Remix's loaders, actions, nested file-based routing, and form-driven mutations for building server-rendered React apps.

SolidJS Cheat Sheet

A reference for SolidJS signals, effects, memos, and control-flow components for building fine-grained reactive UIs without a virtual DOM.

Static vs Instance Methods: What is the Difference?

A static method belongs to the class itself and is called without any object instance, while an instance method belongs to a specific object and operates on th…

What is Method Overriding in OOP?

Method overriding is when a subclass provides its own implementation of a method already defined in its superclass, using the same name and signature.

What is a Virtual Function?

A virtual function is a member function declared in a base class that a derived class can override, with the actual implementation resolved at runtime based on…