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This repository contains my full documentation of Coursera's Introduction to Programming the Internet of Things (IOT) Specialization taught by the professor Ian Harris offered by the University of …
Analyzing Data with Python
This repository features my coursework from the IBM Generative AI Engineering Professional Certificate on Coursera. It includes Jupyter Notebooks with code, explanations, and visualizations, along …
Create Your Own Chatbot Website with Open Source LLMs by cognitiveclass.ai
MIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Softwa…
It will be applied various Data Analytics skills and techniques that wehave learned in the IBM Data Analyst Professional Certificate. It will be assumed the role of an Associate Data Analyst and be…
Answer keys for course - Data Analysis with Python by IBM on Coursera
Data Analysis with Python IBM
To import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. I will then predict future trends from data by deve…
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
吴恩达（Andrew Ng）在coursera的机器学习课程习题的python实现
Machine learning problem sets from Stanford University's Machine Learning course on Coursera
This repository store my lecture notes-and-home work solutions for cs229 machine learning course standford
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
Python Data Science Handbook: full text in Jupyter Notebooks
Empower ML students with hands-on experience. Explore diverse datasets, demystify 'black box' models, and bridge theory with practice. Delve into machine learning with Colab notebooks and in-depth …
A handbook for ML built on answers.
ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy
The notebooks we use on ML course
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
A python library and collection of notebooks for making art with machine learning.
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
🏆 A ranked list of awesome Python open-source libraries and tools. Updated weekly.