#other #computer_vision #deep_learning #e_books #ebook #machine_learning #math #mathematics #nlp #numpy #opencv #opencv_computer_vision #pandas #pdf #python #reinforcement_learning #scikit_learn #scipy #tensorflow

https://github.com/changwookjun/StudyBook

#jupyter_notebook #data_science #machine_learning #python #scikit_learn

https://github.com/justmarkham/scikit-learn-tips

#other #analytics #api #artificial_intelligence #aws #cheatsheet #data_science #data_wrangling #database #deep_learning #linux #machine_learning #neural_network #online_course #python #r #reinforcement_learning #scikit_learn #sql #statistics #visualization

https://github.com/tirthajyoti/Data-science-best-resources

#python #machine_learning #neural_networks #pytorch #scikit_learn #tensor_computation

https://github.com/microsoft/hummingbird

#jupyter_notebook #data_science #keras #machine_learning #nlp #pandas #portfolio #python #scikit_learn

https://github.com/sajal2692/data-science-portfolio

#python #adversarial_machine_learning #artificial_intelligence #attack #catboost #codait #decision_trees #deep_neural_networks #defense_methods #extraction #gradient_boosted_trees #ibm_research #ibm_research_ai #lightgbm #logistic_regression #poisoning #scikit_learn #support_vector_machine #trusted_ai #xgboost

https://github.com/IBM/adversarial-robustness-toolbox

#python #deep_learning #machine_learning #machine_learning_tutorials #pytorch #pytorch_ignite #scikit_learn #sklearn #streamlit #template #tensorflow #webapp #website

https://github.com/jrieke/traingenerator

#jupyter_notebook #python #data_science #machine_learning #scikit_learn #machine_learning_algorithms #ml #machinelearning #machinelearning_python #scikit_learn_python

https://github.com/microsoft/ML-For-Beginners

#python #awesome #awesome_list #best_of #data_science #data_visualization #data_visualizations #deep_learning #keras #machine_learning #nlp #python_library #pytorch #scikit_learn #tensorflow

https://github.com/ml-tooling/best-of-ml-python

#jupyter_notebook #automated_machine_learning #automl #classification #data_science #deep_learning #finetuning #hyperparam #hyperparameter_optimization #jupyter_notebook #machine_learning #natural_language_generation #natural_language_processing #python #random_forest #regression #scikit_learn #tabular_data #timeseries_forecasting #tuning

https://github.com/microsoft/FLAML

#python #data_mining #data_science #forecasting #machine_learning #scikit_learn #time_series #time_series_analysis #time_series_classification #time_series_regression

https://github.com/sktime/sktime

#python #ai #data #data_structures #database #long_term_memory #machine_learning #ml #mlops #mongodb #pytorch #scikit_learn #sklearn #torch #transformers #vector_search

https://github.com/SuperDuperDB/superduperdb

#python #autogluon #automated_machine_learning #automl #computer_vision #data_science #deep_learning #ensemble_learning #forecasting #gluon #hyperparameter_optimization #machine_learning #natural_language_processing #object_detection #python #pytorch #scikit_learn #structured_data #tabular_data #time_series #transfer_learning

AutoGluon makes machine learning easy and fast. With just a few lines of code, you can train and use high-accuracy models for images, text, time series, and tabular data. This means you can quickly build and deploy powerful machine learning models without needing to write a lot of code. It supports Python 3.8 to 3.11 and works on Linux, MacOS, and Windows, making it convenient for various users. This saves time and effort, allowing you to focus on other parts of your project.

https://github.com/autogluon/autogluon

#cplusplus #ai_framework #deep_learning #hardware_acceleration #machine_learning #neural_networks #onnx #pytorch #scikit_learn #tensorflow

ONNX Runtime is a tool that makes machine learning faster and cheaper. It works on many different devices and operating systems, like Windows, Linux, and Mac, and supports popular machine learning frameworks like PyTorch and TensorFlow. This means you can use it to speed up your machine learning models, making your applications run faster and more efficiently. It also helps in training models quickly, especially on powerful NVIDIA GPUs. This benefits you by providing faster customer experiences and lower costs for your machine learning projects.

https://github.com/microsoft/onnxruntime