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Source channel @githubtrending · Post #14717 · May 18

#jupyter_notebook Learning about Large Language Models (LLMs) can be very beneficial. You can build exciting projects over eight weeks, starting with simple tasks and moving to more complex ones. This journey helps you develop deep expertise in AI and LLMs. You'll learn by doing hands-on projects, which is a fun and effective way to understand how these models work. By the end, you'll have skills that can be used in real-world applications, making it a valuable learning experience. https://github.com/ed-donner/llm_engineering

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djangoproject

@djangoproject · Post #507 · 11/26/2017, 10:08 PM

http://devarea.com/machine-learning-with-python-introduction/#.Whs6iCehU8o #Machine_Learning With Python – Introduction #Numpy is package for multi dimension arrays – very effective implementation #Scipy – package for scientific programming , mathematics , signal processing and more #Pandas – package for data handling #Matplotlib – package for data visualization (graphs) #Seaborn – extend Matplotlib with statistical graphs #Scikits – many extensions to spicy for specific fields like x-ray, image processing , deep learning and many more