7389 Open source projects that are alternatives of or similar to Machine Learning Workflow With Python

A New, Interactive Approach to Learning Python

Implementation of Siamese Neural Networks built upon multihead attention mechanism for text semantic similarity task.

U-Net Biomedical Image Segmentation

An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.

A real-time visualisation of the CO2 emissions of electricity consumption

Notebooks for upcoming fastai book (draft / incomplete)

Face recognition and its application as attendance system

A short tutorial on Elmo training (Pre trained, Training on new data, Incremental training)

【火炉炼AI】-机器学习系列文章

R/shiny interface for interactive visualization of data in SummarizedExperiment objects

Tutorials for Fall 2018

Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2020)

Math formula recognition (Images to LaTeX strings)

A GitHub Action that uploads a file to a new release.

A set of jupyter notebooks on pytorch functions with examples

Course materials for teaching data visualization in Python.

Various math-related things in Python code

Command recognition research

Main code for Parcels (Probably A Really Computationally Efficient Lagrangian Simulator)

本项目对中文版《动手学深度学习》中的代码进行了PyTorch实现并整理为PDF版本供下载

A tutorial about Gaussian process regression

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Multiscale Geographically Weighted Regression (MGWR)

A Quick Look generator for Jupyter/IPython notebooks without further dependencies

Stereo convolutional neural network for depth map prediction from stereo images

CS579: Online Social Network Analysis at the Illinois Institute of Technology

Lectures for Udemy - Complete Python Bootcamp Course

This repository contains the Tutorials for the NPTEL MOOC on Machine Learning.

A repo for data science related questions and answers

AI实战-practicalAI 中文版

Repo that contains the supporting material for O'Reilly Webinar "An Intro to Predictive Modeling for Customer Lifetime Value" on Feb 28, 2017

My workflow with ReactJS + Webpack 3+

Using Keras and cats to visualize layers from CNNs

A tutorial on 'Soft weight-sharing for Neural Network compression' published at ICLR2017

This repository contains code for the paper Learning by Association - A versatile semi-supervised training method for neural networks (CVPR 2017) and the follow-up work Associative Domain Adaptation (ICCV 2017).

Machine learning fundamentals lesson in interactive notebooks

Object detection and segmentation for a surgery robot using Mask-RCNN on Python 3, Keras, and TensorFlow..

A recommender system for discovering GitHub repos, built with Apache Spark

Reproduction of "Model-Agnostic Meta-Learning" (MAML) and "Reptile".

Code for the book Deep Learning From Scratch, from O'Reilly September 2019

Modification of fast.ai deep learning course notebooks for usage with Keras 2 and Python 3.

Code for the paper: Fighting Fake News: Image Splice Detection via Learned Self-Consistency

Reusable workflow library for Django

This is a tensorflow re-implementation of Faster R-CNN: Towards Real-Time ObjectDetection with Region Proposal Networks.

Design-of-experiment (DOE) generator for science, engineering, and statistics

Conda environment and package management extension from within Jupyter

StellarGraph - Machine Learning on Graphs

A curated list of applied machine learning and data science notebooks and libraries across different industries.

This Repository contains the list of various Machine and Deep Learning related projects. Related code and data files are available inside this folder. One can go through these projects to implement them in real life for specific use cases.

Python library for identifying the peaks and valleys of a time series.

BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.

An awesome semantic segmentation model that runs in real time