308 Open source projects that are alternatives of or similar to Maml Tf

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

Awesome Multitask Learning Resources

Code for Tensorflow Machine Learning Cookbook

A dataset of datasets for learning to learn from few examples

All Algorithms implemented in R

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

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Meta-Feature Extractor

Curated Tensorflow code resources to help you get started with Deep Learning.

Statistical Machine Intelligence & Learning Engine

[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

Predicting the probability that a diagnosed breast cancer case is malignant or benign based on Wisconsin dataset

Collection for Few-shot Learning

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

An Interactive Approach to Understanding Deep Learning with Keras

The bookdown version lives here: https://bookdown.org/content/3890

🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained

Multivariable regression library in Go

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset

⚡️⚡️⚡️《机器学习实战》代码（基于Python3）🚀

🤖 A portable, header-only, artificial neural network library written in C99

Implementation of a Partial Least Squares Regressor

Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz

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

Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"

[CVPR19] FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image

🎓 Tidy regression tools for academics

mlr3: Machine Learning in R - next generation

A Julia machine learning framework

TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)

Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)

Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

Add linear models including instrumental variable and panel data models that are missing from statsmodels.

Repository for few-shot learning machine learning projects

mlpack: a scalable C++ machine learning library --

A collection of tools for chemometrics and machine learning written in Julia.

Generalized linear models in Julia

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018) (Matlab)

Tribuo - A Java machine learning library

Artificial Neural Network

Automated Machine Learning with scikit-learn

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

"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.

Simple machine learning library / 簡單易用的機器學習套件

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

Implementation of "Make One-Shot Video Object Segmentation Efficient Again” and the semi-supervised fine-tuning "e-OSVOS" approach (NeurIPS 2020).

Shiny dashboard for Land Use Regression modelling

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

Yet another neural network library

Few-shot binary text classification with Induction Networks and Word2Vec weights initialization

A resource list for causality in statistics, data science and physics

Examples use case of PHP-ML library.