Open Machine Learning Course
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Updated
May 27, 2024 - Python
The Jupyter Notebook, previously known as the IPython Notebook, is a language-agnostic HTML notebook application for Project Jupyter. Jupyter notebooks are documents that allow for creating and sharing live code, equations, visualizations, and narrative text together. People use them for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Open Machine Learning Course
A computer vision closed-loop learning platform where code can be run interactively online. 学习闭环《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...) 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页
An AI model that Classifies between 4 classes of Brain Tumors. Well-established CNN architecture pre-trained on a massive dataset of MRI scans. VGG16 model is used for this task.
Specify a github or local repo, github pull request, arXiv or Sci-Hub paper, Youtube transcript or documentation URL on the web and scrape into a text file and clipboard for easier LLM ingestion
Plain python implementations of basic machine learning algorithms
Python course asssignment (2nd year, 2023)
Python package for early warning signals (EWS) of bifurcations in time series data.
Jupyter notebooks in the terminal
Revive Model
This repository keeps my solution for Task 1 in the Introduction to Machine Learning course in Innopolis University. The key technics here are data preprocessing and training ANN on highly imbalanced dataset.
learning dl from karpathy sensei
ipynb renderer for ReactJS
Partial implementation https://arxiv.org/abs/1802.05495
This is where I stash my Python study material.
This repository contains the programs that I worked out in Machine Learning Laboratory.
A neural network which controls a game character.
Several programming exercises (EPs) developed for a College class (MAC 0417 - Image Processing and Visualization)
Example of an application of Naïve Bayes Algorithm.
A sophisticated Machine Learning model, utilizing a range of technical indicators to accurately forecast forthcoming trend reversals with a high degree of confidence. This model is also complemented by an interactive web interface.
Course work code for my university's (SPbPU) course "Computer Architecture".
Created by Fernando Pérez, Brian Granger, and Min Ragan-Kelley
Released December 2011
Latest release 12 days ago