Data Science Roadmap.pdf
15.5 MB
🏷 Comprehensive Data Science Roadmap Notes
✅ This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market.
🕡 From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project.
🕑 How to extract real analysis reports and strategies from raw data using statistics and visualization tools.
🕗 You will learn everything from machine learning and advanced algorithms to precise model evaluation.
🕙 Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world.
🕧 How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for.
🌐 #DataScience #DataScience #pytorch #python #Roadmap
https://xn--r1a.website/CodeProgrammer
✅ This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market.
🕡 From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project.
🕑 How to extract real analysis reports and strategies from raw data using statistics and visualization tools.
🕗 You will learn everything from machine learning and advanced algorithms to precise model evaluation.
🕙 Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world.
🕧 How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for.
🌐 #DataScience #DataScience #pytorch #python #Roadmap
https://xn--r1a.website/CodeProgrammer
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ML Engineer, LLM Engineer, take note: TorchCode
A platform with practice tasks for basic implementations in PyTorch and questions on Transformer, which are often encountered in interviews.
→ Gathers in 39 structured tasks typical for #ML #interviews - implementations of operators, modules, and architectures in #PyTorch.
→ Provides auto-checking, gradient checking, time measurement, and instant feedback, so that the practice more closely resembles #LeetCode for interviews.
→ Built on the basis of Jupyter Notebook, while supporting one-click reset, hints, reference solutions, and progress tracking.
→ Covers such frequent topics as ReLU, Softmax, LayerNorm, Attention, RoPE, Flash Attention, #LoRA, $MoE, and others.
→ Supports online mode via Hugging Face Spaces, opening individual tasks in #Google #Colab, and local launch via #Docker.
👉 https://github.com/duoan/TorchCode
A platform with practice tasks for basic implementations in PyTorch and questions on Transformer, which are often encountered in interviews.
→ Gathers in 39 structured tasks typical for #ML #interviews - implementations of operators, modules, and architectures in #PyTorch.
→ Provides auto-checking, gradient checking, time measurement, and instant feedback, so that the practice more closely resembles #LeetCode for interviews.
→ Built on the basis of Jupyter Notebook, while supporting one-click reset, hints, reference solutions, and progress tracking.
→ Covers such frequent topics as ReLU, Softmax, LayerNorm, Attention, RoPE, Flash Attention, #LoRA, $MoE, and others.
→ Supports online mode via Hugging Face Spaces, opening individual tasks in #Google #Colab, and local launch via #Docker.
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GitHub
GitHub - duoan/TorchCode: 🔥 LeetCode for PyTorch — practice implementing softmax, attention, GPT-2 and more from scratch with instant…
🔥 LeetCode for PyTorch — practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online. - duoan/TorchCode
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📱 TorchCode — a PyTorch training tool for preparing for ML interviews
40 tasks for implementing operators and architectures that are actually asked in interviews. Automatic checking, hints, and reference solutions — all in the browser without installation.
If you're preparing for an ML interview, it's useful to go through at least half of them.
Link: https://github.com/duoan/TorchCode
tags: #useful #pytorch
https://xn--r1a.website/CodeProgrammer✅
40 tasks for implementing operators and architectures that are actually asked in interviews. Automatic checking, hints, and reference solutions — all in the browser without installation.
If you're preparing for an ML interview, it's useful to go through at least half of them.
Link: https://github.com/duoan/TorchCode
tags: #useful #pytorch
https://xn--r1a.website/CodeProgrammer
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