Hands on ML notebook series
Updated our ultimate post with a series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Link: https://github.com/ageron/handson-ml
#wheretostart #opensource #jupyter
Updated our ultimate post with a series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Link: https://github.com/ageron/handson-ml
#wheretostart #opensource #jupyter
GitHub
GitHub - ageron/handson-ml: ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead. - ageron/handson-ml
Machine Learning Engineering with Python.pdf
16.1 MB
Machine Learning Engineering with Python.pdf
Artificial Intelligence ( PDFDrive ).pdf
25.3 MB
Artificial Intelligence ( PDFDrive ).pdf
*Using AI to anticipate others' behavior on the road*
https://techxplore.com/news/2022-04-ai-behavior-road.html
Humans may be one of the biggest roadblocks keeping fully autonomous vehicles off city streets.
If a robot is going to navigate a vehicle safely through downtown Boston, it must be able to predict what nearby drivers, cyclists, and pedestrians are going to do next.
Behavior prediction is a tough problem, however, and current artificial intelligence solutions are either too simplistic (they may assume pedestrians always walk in a straight line), too conservative (to avoid pedestrians, the robot just leaves the car in park), or can only forecast the next moves of one agent (roads typically carry many users at once.)
https://techxplore.com/news/2022-04-ai-behavior-road.html
Humans may be one of the biggest roadblocks keeping fully autonomous vehicles off city streets.
If a robot is going to navigate a vehicle safely through downtown Boston, it must be able to predict what nearby drivers, cyclists, and pedestrians are going to do next.
Behavior prediction is a tough problem, however, and current artificial intelligence solutions are either too simplistic (they may assume pedestrians always walk in a straight line), too conservative (to avoid pedestrians, the robot just leaves the car in park), or can only forecast the next moves of one agent (roads typically carry many users at once.)
Tech Xplore
Using AI to anticipate others' behavior on the road
Humans may be one of the biggest roadblocks keeping fully autonomous vehicles off city streets.
Researchers Introduce A Machine-Learning System Called M2I That Efficiently Predicts The Future Trajectories of Multiple Road Users, Enabling Autonomous Vehicles To Navigate Safely
Quick Read: https://www.marktechpost.com/2022/04/26/researchers-introduce-a-machine-learning-system-called-m2i-that-efficiently-predicts-the-future-trajectories-of-multiple-road-users-enabling-autonomous-vehicles-to-navigate-safely/
Code: https://github.com/Tsinghua-MARS-Lab/M2I
Project: https://tsinghua-mars-lab.github.io/M2I/
Project: https://arxiv.org/pdf/2202.11884.pdf
Quick Read: https://www.marktechpost.com/2022/04/26/researchers-introduce-a-machine-learning-system-called-m2i-that-efficiently-predicts-the-future-trajectories-of-multiple-road-users-enabling-autonomous-vehicles-to-navigate-safely/
Code: https://github.com/Tsinghua-MARS-Lab/M2I
Project: https://tsinghua-mars-lab.github.io/M2I/
Project: https://arxiv.org/pdf/2202.11884.pdf
MarkTechPost
Researchers Introduce A Machine-Learning System Called M2I That Efficiently Predicts The Future Trajectories of Multiple Road Users…
This Article Is Based On The Research Paper 'M2I: From Factored Marginal Trajectory Prediction to Interactive Prediction' and MIT article. All Credit For This Research Goes To The Researchers Of This Paper 👏👏👏 Please Don't Forget To Join Our ML Subreddit…
5_6282731757485687955.pdf
1.7 MB
I am sharing '5_6282731757485687955' with you
OPT: Open Pre-trained Transformer Language Models
Zhang et al.: https://arxiv.org/abs/2205.01068
#DeepLearning #Transformer #LanguageModels
Zhang et al.: https://arxiv.org/abs/2205.01068
#DeepLearning #Transformer #LanguageModels
50 Free Data Science Cheatsheets. ✔️ 1. Python : https://lnkd.in/grD8XUS6 2. Pandas : https://lnkd.in/g4yTJ7CP 3. NumPy : https://lnkd.in/gg9Uw-km 4. Matplotlib : https://lnkd.in/gahrGicD 5. Seaborn : https://lnkd.in/gcu4UKpw 6. Scikit-learn : https://lnkd.in/gGfkNu5i 7. TensorFlow : https://lnkd.in/g3fw3uRV 8. Keras : https://lnkd.in/gfPTfbgg 9. PyTorch : https://ow.ly/6TQI50PjRA5 10. SQL : https://lnkd.in/gnwe4qcb 11. GeoPandas : https://lnkd.in/d-hnRaJt 12. Git : https://lnkd.in/gyzhztvH 13. AWS : https://bit.ly/3ZQWMS1 14. Azure : https://bit.ly/42f4N4V 15. Google Cloud Platform : https://bit.ly/3JJADzv 16. Docker : https://bit.ly/3Lt2zJe 17. Kubernetes : https://lnkd.in/gjXCT7Mb 18. Linux Command Line : https://bit.ly/3FtcTgw 19. Jupyter Notebook : https://lnkd.in/g7cPmgHQ 20. Data Wrangling : https://bit.ly/3TiMibP 21. Data Visualization : https://lnkd.in/gQ52Jd_J 22. Statistical Inference : https://lnkd.in/grNXVQh5 23. Probability : https://lnkd.in/gvnWCphc 24. Linear Algebra : https://lnkd.in/gty6XpVF 25. Calculus : https://lnkd.in/gjhsmsxu 26. Time Series : https://bit.ly/3Fvuep4 27. NLP : https://bit.ly/3Fvursm 28. Neural Network : https://lnkd.in/gThs2AAp 29. Deep Learning : https://lnkd.in/gVbSPae2 30. Machine Learning : https://bit.ly/3mZ5Wh3 31. Apache Spark : https://lnkd.in/ge7Rj-Yr 32. Hadoop : https://bit.ly/3Lq34DR 33. Big-O Notation : https://lnkd.in/gfYqM8WU 34. Regular Expression : https://lnkd.in/gE9kZTZW 35. Unix/Linux Permissions : https://bit.ly/3ZUfwA8 36. Python String Formatting : https://lnkd.in/d4s3W779 37. Flask : https://lnkd.in/gGzbSTgU 38. Django : https://lnkd.in/grZcWz8y 39. Plotly : https://lnkd.in/d8SKxbdA 40. PostgreSQL : https://lnkd.in/gzfiW7zB 41. MySQL : https://lnkd.in/g4JnPVTe 42. MongoDB : https://lnkd.in/gHc4F4ER 43. TensorFlow Probability Cheat Sheet : https://lnkd.in/gr3bgDGP 44. OpenAI GPT-3 Documentation : https://lnkd.in/gawB_SC9 45. GPT-3 API Reference : https://lnkd.in/gtCGZvX8 46. SciPy : https://ow.ly/JYCN50PjRG7 47. Chat GPT Cheat Sheet : https://lnkd.in/e43cDB9q 48. Colors in dataviz : https://lnkd.in/dWU6WkhU 49. Geospatial data science in Python : https://lnkd.in/gCbqNXFn 50. Network analysis : https://ow.ly/fYm550PjRyf
lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn