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- Front-end: HTML, CSS, Responsive Design (Bootstrap, Flexbox Grid), Tailwind CSS , JavaScript, TypeScript, React.js, Next.js
- Back-end: Node.js, Express.js, RESTful APIs, Postman, GraphQL
- Databases: SQL (MySQL, PostgreSQL), NoSQL (MongoDB)
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- Data Analysis & Visualization Libraries: Pandas, NumPy, Matplotlib, Seaborn
- Frameworks: Scikit-learn, TensorFlow, Keras, PyTorch
- Algorithms & Techniques:
- Supervised Learning and Unsupervised Learning, Deep Learning, Neural Networks, Reinforcement Learning, Recommender Systems
- Model Evaluation and Validation: Cross-Validation, Confusion Matrix
- Additional : Flask, NLP
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Blockchain Development:
- Technologies: Blockchain, Web3, Ether.js, Smart Contracts (Solidity, Rust), Ethereum, Hyperledger, Layer 2
- Standards and Tokens: ERC Standards (ERC20, ERC721), Tokens, OpenZeppelin
- Optimization and Cryptography: Gas Optimization, Cryptography (SHA-256, Public/Private Key Encryption)
- Applications and Platforms: NFT, DApps, DeFi, DAO, Staking, Chainlink, IPFS, Filecoin
- Algorithms and Concepts: Merkle Tree, Consensus Algorithms (PoW, PoS, DPoS)
- Blockchains: Ethereum, Binance Smart Chain
Tools and Libraries:
- Hardhat, Metamask, Alchemy, Remix IDE, Truffle Suite, Ganache
ptl-harsh / deep-learning-keras-tf-tutorial Goto Github PK
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Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.
Home Page: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO