atkachivska Goto Github PK
Name: Angelina Martinovych
Type: User
Name: Angelina Martinovych
Type: User
Advanced Deep Learning with Keras, published by Packt
Documentation and helpful resources for calling the Analytics 1.4 Apis
A curated list of Gradient Boosting resources for Data Scientists
A distributed approach for data exploration, neural net training prediction and scoring. The modules are intended to handle large datasets by only operating in batches. The specific problem studied here is related to predicting the churn ratio (i.e., the amount of customers that leave a service) from a telecommunications company.
Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.
# Deep Learning with Keras
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
A collection of various deep learning architectures, models, and tips
Distributed Deep learning with Keras & Spark
this repository accompanies the book "Grokking Deep Learning"
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Official PyTorch implementation of "I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image", ECCV 2020
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Project Molten is the precurssor to Project Deliquesces. The goal is to be able to predict the melting point of a given molecule. The model receives integerized SMILES strings labeled with the normalized melting point temperates.
Machine learning course at MIPT
Open Machine Learning Course https://mlcourse.ai
Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Machine learning, in numpy
Learning to predict taxi fares in the online setting. Intention of the project was to compare the performance of online vs offline machine learning algorithms in terms of accuracy, efficiency and speed.
python library for easy data science
PyTorch Tutorial for Deep Learning Researchers
Build your neural network easy and fast
Use of Neural Network in Regression problem written in Keras API.
5 machine learning techniques to forecast product sales
Always sparse. Never dense. But never say never. A repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
Материалы мини-курса на Stepik "Нейронные сети и обработка текста"
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.