6550 Open source projects that are alternatives of or similar to Prediciting Binary Options

IPython widgets, interactive plots, interactive machine learning

A collection of all projects pertaining to different layers in the SDC software stack

An Interactive Approach to Understanding Deep Learning with Keras

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Virgilio is developed and maintained by these awesome people. You can email us virgilio.datascience (at) gmail.com or join the Discord chat.

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn and TPOT.

An implementation of multivariate projection pursuit regression and univariate classification

Compilation of R and Python programming codes on the Data Professor YouTube channel.

An open-source, low-code machine learning library in Python

The "Python Machine Learning (3rd edition)" book code repository

a sklearn wrapper for Google's BERT model

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Fast and memory-efficient clustering

Machine Learning and NLP: Text Classification using python, scikit-learn and NLTK

An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP

Stanford Machine Learning course exercises implemented with scikit-learn

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Github repo with tutorials to fine tune transformers for diff NLP tasks

food image to recipe with deep convolutional neural networks.

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

My blogs and code for machine learning. http://cnblogs.com/pinard

A scikit-learn based module for multi-label et. al. classification

Machine Learning and Reinforcement Learning in Finance New York University Tandon School of Engineering

📚 Various cheatsheets in PDF

Machine Learning Tutorials in Python

Jupyter Notebook exercises for k-means clustering with Python 3 and scikit-learn

A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.

Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

Kaggle Struggle

📓 deepleaning and cv notes.

Text processing library for sentiment analysis and related tasks

fastai V2 implementation of Timeseries classification papers.

Python Machine Learning Algorithms

Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

BERT-NER (nert-bert) with google bert https://github.com/google-research.

機器學習: Python

Python package for Bayesian Machine Learning with scikit-learn API

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

Zeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark

Skin cancer classification using Inceptionv3

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Repository for the ICON 2017 hackathon 'multivoxel pattern analysis (MVPA) of fMRI data in Python'

Service Classification based on Service Description

The "Python Machine Learning (2nd edition)" book code repository and info resource

Association Rule Mining from Spatial Data for Crime Analysis

The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.

brief introduction to Python for machine learning

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

🛠 All-in-one web-based IDE specialized for machine learning and data science.