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Claude Code for Beginners: Step-by-Step AI Coding Tutorial

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 Artificial Intelligence is changing how developers write software. From generating code to fixing bugs and explaining complex logic, AI tools are becoming everyday companions for programmers. One such powerful tool is Claude Code , powered by Anthropic’s Claude AI model. If you’re a beginner or  an experienced developer looking to improve productivity, this guide will help you understand  what Claude Code is, how it works, and how to use it step-by-step . Let’s get started. What is Claude Code? Claude Code is an AI-powered coding assistant built on top of Anthropic’s Claude models. It helps developers by: Writing code from natural language prompts Explaining existing code Debugging errors Refactoring code for better readability Generating tests and documentation In simple words, you describe what you want in plain English, and Claude Code helps turn that into working code. It supports multiple programming languages, such as: Python JavaScri...
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20 Best Videos to Learn Machine Learning Quickly

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According to Coursera -Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.

1.     introduction, The Motivation Applications of Machine Learning
2.     An Application of Supervised Learning - Autonomous Deriving
3.     The Concept of Underfitting and Overfitting
4.     Newtons Method
5.     Discriminative Algorithms
6.     Multinomial Event Model
7.     Optimal Margin Classifier
8.     Kernels
9.     Bias/variance Tradeoff
10. Uniform Convergence - The Case of Infinite H
11. Bayesian Statistics and Regularization
12. The Concept of Unsupervised Learning
13. Mixture of Gaussian
14. The Factor Analysis Model
15. Latent Semantic Indexing (LSI)
16. Applications of Reinforcement Learning
17. Generalization to the Continuous States
18. State-action Rewards
19. Advice for Applying Machine Learning
20. Partially Observable MDPs (POMDPs)

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