state-of-the-art-result-for-machine-learning-problems
Machine Learning Benchmarks
A collection of state-of-the-art results for various machine learning problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
9k stars
872 watching
1k forks
last commit: over 5 years ago
Linked from 1 awesome list
jacksu/machine-learningRelated projects:
| Repository | Description | Stars |
|---|---|---|
 openai/gpt-2 | A repository providing code and models for research into language modeling and multitask learning | 22,516 |
 dotnet/machinelearning | A cross-platform machine learning framework for .NET that enables developers to build, train, and deploy models without prior expertise in ML. | 9,035 |
 eriklindernoren/ml-from-scratch | Provides implementations of fundamental machine learning models and algorithms from scratch in Python | 24,003 |
 labmlai/annotated_deep_learning_paper_implementations | Implementations of various deep learning algorithms and techniques with accompanying documentation | 56,215 |
| dotnet/machinelearning-samples | A collection of samples and examples demonstrating the usage of ML.NET for machine learning tasks in .NET applications. | 4,490 |
 hoya012/deep_learning_object_detection | A comprehensive repository of object detection papers and datasets using deep learning techniques | 11,316 |
 sahith02/machine-learning-algorithms | A comprehensive resource for machine learning and deep learning algorithms | 292 |
 firmai/industry-machine-learning | A curated collection of machine learning and data science projects applied to various industries. | 7,258 |
 haifengl/smile | A comprehensive machine learning and data science toolkit with algorithms for classification, regression, clustering, and more. | 6,046 |
 microsoft/synapseml | A library for building scalable machine learning pipelines on distributed computing frameworks like Apache Spark | 5,068 |
 trekhleb/homemade-machine-learning | Practices implementing popular machine learning algorithms from scratch to gain a deeper understanding of their mathematics | 23,121 |
 dair-ai/ml-papers-explained | An explanation of key concepts and advancements in the field of Machine Learning | 7,315 |
 sebastianruder/nlp-progress | A comprehensive repository tracking progress in NLP tasks and their corresponding datasets. | 22,715 |
 christophm/interpretable-ml-book | A comprehensive resource for explaining the decisions and behavior of machine learning models. | 4,794 |
 mhagiwara/100-nlp-papers | A curated collection of 100 essential NLP papers for researchers and developers to understand the foundations of natural language processing | 3,751 |