Archives for python libraries - Page 3
One of the issues of using Python for data analytics is the inability to create shareable data visualization reports quickly. Other analytics tools like PowerBI and Tableau can readily publish and share reports. Sure, you can create shareable reports with modules like dash and Flask but they require quite a bit of extra code. Datapane…
The post Creating Interactive Data Reports With Datapane appeared first on Analytics India Magazine.
Localized Randomized Affine Shadowsampling (LoRAS) locally approximates the manifold by generating a random convex combination of noisy minority class data points.
The post Hands-on Guide to LoRAS: A Better Oversampling Algorithm appeared first on Analytics India Magazine.
CoreMLTools is a framework created by Apple that allows you to convert models from third-party libraries to the Core ML format.
The post Converting PyTorch and TensorFlow Models into Apple Core ML using CoreMLTools appeared first on Analytics India Magazine.
Spleeter is a source separation Python library created by the Deezer R&D team for various types of source separation tasks.
The post Overview of Spleeter: A Music Source Separation Engine appeared first on Analytics India Magazine.
Orbit is an open-source Python framework created by Uber for Bayesian time series forecasting and inference.
The post Hands-on Guide to Orbit: Uber’s Python Framework For Bayesian Forecasting & Inference appeared first on Analytics India Magazine.
Torch-Points3D is a flexible and powerful framework that aims to make deep learning on 3D data both more accessible and reproducible.
The post Hands-On Guide to Torch-Points3D: A Modular Deep Learning Framework for 3D Data appeared first on Analytics India Magazine.
TensorFlow, Pytorch, Caffe, Keras, Theano, and many more. There’s already an abundance of deep learning frameworks, so why should you care about Trax? Well, most deep learning libraries have two major drawbacks: They require you to write long syntaxes, even for simple tasks. Their language/API can be quite complex and hard to understand, especially for…
The post What is Trax and How is it a Better Framework for Advanced Deep Learning? appeared first on Analytics India Magazine.
Ever since Google has publicised Tensorflow, its application in Deep Learning has been increasing tremendously. It is used even more in research and production for authoring ML algorithms. Though it is flexible, it does not provide an end-to-end production system. On the other hand, Sibyl has end-to-end facilities but lacks flexibility. Google then came up…
The post Guide to TensorFlow Extended(TFX): End-to-End Platform for Deploying Production ML Pipelines appeared first on Analytics India Magazine.
This post is in continuation with our previous article about Alchemy, the very first benchmark on meta-Reinforcement Learning. Deepmind with the University of London has released an open-source benchmark environment for meta-RL : Alchemy: A structured task distribution for meta-reinforcement learning by Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck,…
The post Hands-on Alchemy: A Structured Task Distribution for Meta-Reinforcement Learning appeared first on Analytics India Magazine.
Sktime is a unified python framework/library providing API for machine learning with time series data and sklearn compatible tools to analyse, visualize, tune and validate multiple time series learning models such as time series forecasting, time series regression and classification.
The post Guide To Sktime – Python Library For Time Series Data (Compatible With Sci-kit learn) appeared first on Analytics India Magazine.