Free guides, cheatsheets, tools, and career resources to accelerate your AI journey.
A complete walkthrough of AI fundamentals — concepts, terminology, and real-world applications.
Step-by-step path from Python basics to deploying ML models in production.
Covers data wrangling, EDA, visualization, and statistical modeling with practical examples.
Key libraries, syntax, and patterns — NumPy, Pandas, Matplotlib at a glance.
Essential SQL queries, joins, aggregations, and window functions in one sheet.
Activation functions, loss functions, optimizers, and key architecture diagrams.
5-part series covering perceptrons, backpropagation, and CNNs with code walkthroughs.
End-to-end tutorial: intent recognition, NLP pipeline, and deploying with FastAPI.
Image processing, object detection, and face recognition from scratch.
Upload your resume and get instant feedback on ATS score, keywords, and improvements.
Answer a few questions and get a personalized AI & tech career roadmap.
Browse curated public datasets for practice projects in ML and data science.
Top 100 interview questions with model answers for data science and ML roles.
How to write a profile that gets noticed by AI/ML recruiters.
10 project ideas across computer vision, NLP, and predictive analytics to build your portfolio.
Industry trends, job market analysis, and skill demand report for the Indian AI ecosystem.
From GPT-4 to multimodal models — key advancements explained for practitioners.
Bias, fairness, and responsible AI — a practical guide for developers and researchers.
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