Supercharged Coding with #GenAI โ From vibe coding to best practices using GitHub Copilot, ChatGPT, and OpenAI: http://
amzn.to/3VBH2Su v/ @PacktDataML ๐๐ฎ๐ ๐๐ฎ๐ช๐ฝ๐พ๐ป๐ฎ๐ผ: Discover how GitHub Copilot, ChatGPT, and the OpenAI API can boost your coding productivity Push
RESEARCH
-
Self-Reflection and Questioning Thoughts Fuel Real Progress in AI
By
–
-
Modern Python Cookbook: 818 Pages with 130+ Data Science Recipes
By
–
Modern Python Cookbook (818 pages, 130+ recipes, 3rd Edition): http://
amzn.to/47l2lz1 v/ @PacktDataML โโโโโโ
#DataScience #DataScientist #MachineLearning #ML #ComputationalScience #Simulation -
Dancing with Qubits: Quantum Computing Journey Second Edition
By
–
Dancing with Qubits โ From qubits to algorithms, embark on the Quantum Computing journey shaping our future: http://
amzn.to/4bJNwFj [2nd Edition] v/ @PacktDataML Covers Quantum #MachineLearning and AI โโโโ
#ComputerScience #ML #ComputationalScience -
Developing Kaggle Notebooks Toward Grandmaster Status
By
–
+ see this โDeveloping Kaggle Notebooks, toward becoming a @Kaggle Notebooks Grandmasterโ at: http://
amzn.to/48LAjKA by @PredaGabi v/ @PacktDataML โโโโโโ
#DataScience #MachineLearning #ML #DataScientist #Python -
Kaggle Workbook: Self-Learning Exercises for Data Science Competitions
By
–
โThe Kaggle Workbook: Self-Learning Exercises and Valuable Insights for @Kaggle #DataScience Competitions": http://
amzn.to/41jKa7r by @tng_konrad and @LucaMassaron โโโโโโ
#Analytics #DataScientist #AI #DeepLearning #ML #MachineLearning #Python -
Transformers for NLP and Vision: Generative AI and LLMs Guide
By
–
Very impressive! >> "Transformers for #NLProc and Computer Vision: Explore Generative AI and Large Language Models #LLMs with Hugging Face, GPT-4V, DALL-E 3,…" [3rd Edition] http://
amzn.to/3TkBknI
โโโโ
Huge, 728 pages of #AI #DeepLearning #MachineLearning #DataScience joy! -
Predictive Statistics: Beyond Models Analysis and Inference
By
–
Predictive #Statistics โ Analysis and Inference beyond Models: http://
amzn.to/49TYu9v
โโโโโ
#Probability #DataScience #Mathematics #MachineLearning #ML #DataScientist -
Machine Learning with R: Complete Guide to Model Building and Tuning
By
–
#MachineLearning with R โ Techniques for building & improving #ML models, from data preparation to model tuning, evaluation, & working with big data (4th Edition. Huge 762 pages) available at https://
amzn.to/45sDq98 โโโโ
#Rstats #DataScience #Analytics #DataScientist -
Python Feature Engineering Cookbook 3rd Edition Released
By
–
3rd Edition! "Python Feature Engineering Cookbook", complete guidebook with recipes for crafting powerful features for #MachineLearning models: http://
amzn.to/4rDWUT9 by @Soledad_Galli Her course: https://
trainindata.com/p/feature-engi
neering-for-machine-learning
โฆ
โโ
#AI #ML #DataLiteracy #DataScience #DataScientist -
Hidden Complexities of Adding Tools to Multi-Agent Systems
By
–
What actually happens when you add a 'tool' to a multi-agent system? If you work with agents, you know this feeling, the change takes minutes. The consequences take days to debug. Here are the 3 hidden complexities no one talks about: The Agent's Decision Space Explodes