Forwarded from Machine Learning with Python
10 GitHub repos to build a career in AI engineering:
(100% free step-by-step roadmap)
1οΈβ£ ML for Beginners by Microsoft
A 12-week project-based curriculum that teaches classical ML using Scikit-learn on real-world datasets.
Includes quizzes, lessons, and hands-on projects, with some videos.
GitHub repo β https://lnkd.in/dCxStbYv
2οΈβ£ AI for Beginners by Microsoft
This repo covers neural networks, NLP, CV, transformers, ethics & more. There are hands-on labs in PyTorch & TensorFlow using Jupyter.
Beginner-friendly, project-based, and full of real-world apps.
GitHub repo β https://lnkd.in/dwS5Jk9E
3οΈβ£ Neural Networks: Zero to Hero
Now that youβve grasped the foundations of AI/ML, itβs time to dive deeper.
This repo by Andrej Karpathy builds modern deep learning systems from scratch, including GPTs.
GitHub repo β https://lnkd.in/dXAQWucq
4οΈβ£ DL Paper Implementations
So far, you have learned the fundamentals of AI, ML, and DL. Now study how the best architectures work.
This repo covers well-documented PyTorch implementations of 60+ research papers on Transformers, GANs, Diffusion models, etc.
GitHub repo β https://lnkd.in/dTrtDrvs
5οΈβ£ Made With ML
Now itβs time to learn how to go from notebooks to production.
Made With ML teaches you how to design, develop, deploy, and iterate on real-world ML systems using MLOps, CI/CD, and best practices.
GitHub repo β https://lnkd.in/dYyjjBGb
6οΈβ£ Hands-on LLMs
- You've built neural nets.
- You've explored GPTs and LLMs.
Now apply them. This is a visually rich repo that covers everything about LLMs, like tokenization, fine-tuning, RAG, etc.
GitHub repo β https://lnkd.in/dh2FwYFe
7οΈβ£ Advanced RAG Techniques
Hands-on LLMs will give you a good grasp of RAG systems. Now learn advanced RAG techniques.
This repo covers 30+ methods to make RAG systems faster, smarter, and accurate, like HyDE, GraphRAG, etc.
GitHub repo β https://lnkd.in/dBKxtX-D
8οΈβ£ AI Agents for Beginners by Microsoft
After diving into LLMs and mastering RAG, learn how to build AI agents.
This hands-on course covers building AI agents using frameworks like AutoGen.
GitHub repo β https://lnkd.in/dbFeuznE
9οΈβ£ Agents Towards Production
The above course will teach what AI agents are. Next, learn how to ship them.
This is a practical playbook for building agents covering memory, orchestration, deployment, security & more.
GitHub repo β https://lnkd.in/dcwmamSb
π AI Engg. Hub
To truly master LLMs, RAG, and AI agents, you need projects.
This covers 70+ real-world examples, tutorials, and agent app you can build, adapt, and ship.
GitHub repo β https://lnkd.in/geMYm3b6
(100% free step-by-step roadmap)
A 12-week project-based curriculum that teaches classical ML using Scikit-learn on real-world datasets.
Includes quizzes, lessons, and hands-on projects, with some videos.
GitHub repo β https://lnkd.in/dCxStbYv
This repo covers neural networks, NLP, CV, transformers, ethics & more. There are hands-on labs in PyTorch & TensorFlow using Jupyter.
Beginner-friendly, project-based, and full of real-world apps.
GitHub repo β https://lnkd.in/dwS5Jk9E
Now that youβve grasped the foundations of AI/ML, itβs time to dive deeper.
This repo by Andrej Karpathy builds modern deep learning systems from scratch, including GPTs.
GitHub repo β https://lnkd.in/dXAQWucq
So far, you have learned the fundamentals of AI, ML, and DL. Now study how the best architectures work.
This repo covers well-documented PyTorch implementations of 60+ research papers on Transformers, GANs, Diffusion models, etc.
GitHub repo β https://lnkd.in/dTrtDrvs
Now itβs time to learn how to go from notebooks to production.
Made With ML teaches you how to design, develop, deploy, and iterate on real-world ML systems using MLOps, CI/CD, and best practices.
GitHub repo β https://lnkd.in/dYyjjBGb
- You've built neural nets.
- You've explored GPTs and LLMs.
Now apply them. This is a visually rich repo that covers everything about LLMs, like tokenization, fine-tuning, RAG, etc.
GitHub repo β https://lnkd.in/dh2FwYFe
Hands-on LLMs will give you a good grasp of RAG systems. Now learn advanced RAG techniques.
This repo covers 30+ methods to make RAG systems faster, smarter, and accurate, like HyDE, GraphRAG, etc.
GitHub repo β https://lnkd.in/dBKxtX-D
After diving into LLMs and mastering RAG, learn how to build AI agents.
This hands-on course covers building AI agents using frameworks like AutoGen.
GitHub repo β https://lnkd.in/dbFeuznE
The above course will teach what AI agents are. Next, learn how to ship them.
This is a practical playbook for building agents covering memory, orchestration, deployment, security & more.
GitHub repo β https://lnkd.in/dcwmamSb
To truly master LLMs, RAG, and AI agents, you need projects.
This covers 70+ real-world examples, tutorials, and agent app you can build, adapt, and ship.
GitHub repo β https://lnkd.in/geMYm3b6
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π₯ Trending Repository: tensorzero
π Description: TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation.
π Repository URL: https://github.com/tensorzero/tensorzero
π Website: https://tensorzero.com
π Readme: https://github.com/tensorzero/tensorzero#readme
π Statistics:
π Stars: 9.9K stars
π Watchers: 73
π΄ Forks: 664 forks
π» Programming Languages: Rust - TypeScript - Python - Jupyter Notebook - Go - Shell
π·οΈ Related Topics:
==================================
π§ By: https://t.me/DataScienceM
π Description: TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation.
π Repository URL: https://github.com/tensorzero/tensorzero
π Website: https://tensorzero.com
π Readme: https://github.com/tensorzero/tensorzero#readme
π Statistics:
π Stars: 9.9K stars
π Watchers: 73
π΄ Forks: 664 forks
π» Programming Languages: Rust - TypeScript - Python - Jupyter Notebook - Go - Shell
π·οΈ Related Topics:
#python #rust #machine_learning #ai #deep_learning #ml #artificial_intelligence #openai #llama #gpt #mlops #ml_engineering #ai_engineering #large_language_models #llm #llms #generative_ai #llmops #anthropic #genai
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π§ By: https://t.me/DataScienceM
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π₯ Trending Repository: airflow
π Description: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
π Repository URL: https://github.com/apache/airflow
π Website: https://airflow.apache.org/
π Readme: https://github.com/apache/airflow#readme
π Statistics:
π Stars: 41.9K stars
π Watchers: 764
π΄ Forks: 15.5K forks
π» Programming Languages: Python - TypeScript - JavaScript - Shell - Dockerfile - Jinja
π·οΈ Related Topics:
==================================
π§ By: https://t.me/DataScienceM
π Description: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
π Repository URL: https://github.com/apache/airflow
π Website: https://airflow.apache.org/
π Readme: https://github.com/apache/airflow#readme
π Statistics:
π Stars: 41.9K stars
π Watchers: 764
π΄ Forks: 15.5K forks
π» Programming Languages: Python - TypeScript - JavaScript - Shell - Dockerfile - Jinja
π·οΈ Related Topics:
#python #workflow #data_science #machine_learning #airflow #automation #etl #workflow_engine #scheduler #apache #orchestration #data_engineering #data_integration #elt #data_pipelines #dag #apache_airflow #mlops #workflow_orchestration #data_orchestrator
==================================
π§ By: https://t.me/DataScienceM
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π₯ Trending Repository: agent-lightning
π Description: The absolute trainer to light up AI agents.
π Repository URL: https://github.com/microsoft/agent-lightning
π Website: https://microsoft.github.io/agent-lightning/
π Readme: https://github.com/microsoft/agent-lightning#readme
π Statistics:
π Stars: 2K stars
π Watchers: 11
π΄ Forks: 170 forks
π» Programming Languages: Python
π·οΈ Related Topics:
==================================
π§ By: https://t.me/DataScienceM
π Description: The absolute trainer to light up AI agents.
π Repository URL: https://github.com/microsoft/agent-lightning
π Website: https://microsoft.github.io/agent-lightning/
π Readme: https://github.com/microsoft/agent-lightning#readme
π Statistics:
π Stars: 2K stars
π Watchers: 11
π΄ Forks: 170 forks
π» Programming Languages: Python
π·οΈ Related Topics:
#agent #reinforcement_learning #mlops #llm #agentic_ai
==================================
π§ By: https://t.me/DataScienceM
π₯ Trending Repository: agent-starter-pack
π Description: Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.
π Repository URL: https://github.com/GoogleCloudPlatform/agent-starter-pack
π Website: https://googlecloudplatform.github.io/agent-starter-pack/
π Readme: https://github.com/GoogleCloudPlatform/agent-starter-pack#readme
π Statistics:
π Stars: 3.9K stars
π Watchers: 53
π΄ Forks: 1.1K forks
π» Programming Languages: Python - Jupyter Notebook - HCL - TypeScript - SCSS - Makefile
π·οΈ Related Topics:
==================================
π§ By: https://t.me/DataScienceM
π Description: Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.
π Repository URL: https://github.com/GoogleCloudPlatform/agent-starter-pack
π Website: https://googlecloudplatform.github.io/agent-starter-pack/
π Readme: https://github.com/GoogleCloudPlatform/agent-starter-pack#readme
π Statistics:
π Stars: 3.9K stars
π Watchers: 53
π΄ Forks: 1.1K forks
π» Programming Languages: Python - Jupyter Notebook - HCL - TypeScript - SCSS - Makefile
π·οΈ Related Topics:
#gcp #gemini #agents #observability #mlops #generative_ai #llmops #genai_agents
==================================
π§ By: https://t.me/DataScienceM
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