1974 Machine Learning! @bigdataconf A Greater Foundation for Machine Learning. Welcome to Python, TensorFlow, and PyTorch. Register and join me in the new year. Join and learn at your own pace. Machine Learning for all the ages. @bigdataconf #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/Greater-MLearn
MIT: 35 Best Courses in Machine Learning! @MIT Explore a world of knowledge with free online courses from MIT on edX, featuring lessons in AI, machine learning, computer science engineering, circuits and electronics, Genetics, data science, statistics and much more. Many people are unaware that edX hosts an incredible collection of free online courses from some of the top educational institutions globally. You can dive into everything from AI to Python programming without any cost. A significant number of these courses are crafted by MIT experts. We highly encourage you to take advantage of this opportunity, and to kickstart your learning journey, here’s a curated selection of the best free online courses from MIT that you can explore this month. #Bigdata #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode References Green, J. (2024, December 11). MIT: 35 best courses in machine learning! @MIT_CSAIL Mashable. Retrieved December 11, 2024, from mashable.com/article/free-mi…
GPT with LangGraph! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode The rapid advancement of large model technology is leading to an increasing application of agent technology across various fields and industries significantly transforming how people work and live. In complex and dynamic environments, multi-agent systems are able to tackle intricate tasks that would be challenging for a single agent, thanks to their collaborative and division-of-labor approaches. The following stack of research papers and hands on tutorials highlight the integrated use of GPT with LangGraph and CrewAI. LangGraph enhances information transmission efficiency through its graph-based structure, while CrewAI boosts team collaboration and system performance via intelligent task allocation and resource management. The key areas of this research include: The design of agent architectures based on LangGraph for precise control . The enhancement of agent capabilities through CrewAI to tackle a range of tasks. The goal of this study is to explore the combined potential of GPT and LangGraph and CrewAI in multi-agent systems, offering fresh insights for the ongoing evolution of agent technology and fostering innovation in the application of large model intelligent agents. References Duan, Z., & Wang, J. (2024, November 27). Exploration of LLM multi-agent application implementation based on LangGraph+CrewAI. arXiv. Retrieved March 9, 2025, from arxiv.org/abs/2411.18241 Horsey, J. (2025, March 9). Build a powerful Python chatbot in minutes with LangGraph. Geeky Gadgets. Retrieved March 9, 2025, from geeky-gadgets.com/build-a-po… Ong, R. (2024, July 10). GPT-4o and LangGraph tutorial: Build a TNT-LLM application. DataCamp. Retrieved March 9, 2025, from datacamp.com/tutorial/gpt-4o… Sivan, V. (2024). Building AI agent systems with LangGraph. Medium. Retrieved March 9, 2025, from medium.com/pythoneers/buildi… Wang, J., & Duan, Z. (2024, December 2). Intelligent Spark agents: A modular LangGraph framework for scalable, visualized, and enhanced big data machine learning workflows. arXiv. Retrieved March 9, 2025, from arxiv.org/abs/2412.01490