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Training and serving large-scale neural networks
The Fuzzy Labs guide to the universe of open source MLOps
Reinforcement learning resources curated
Run your code in the cloud, with technology so advanced, it feels like magic!
Solutions to Programming Assignments for Bioinformatics Algorithms (Part 1) on Coursera.org
Most proteins localize to specific regions where they perform their biological function. Fluorescent microscopy can reveal the subcellular localization patterns of tagged proteins. The goal of this project is to use active learning to build a classifier that capable of classifying bioimages (encoded as feature vectors) according to subcellular localization patterns. There are three data pools: Easy: A low-noise data pool Moderate: This pool has some noise (labels and features) Difficult: The points in this pool have a larger number of features than those in the easy and moderate pools. Some of these features are irrelevant. Your algorithm will need to perform active learning and feature selection. Each data pool consists of 4120 training images and 1000 test images. Each image is represented as a feature vector (you do not need to do feature extraction yourself). There are 8 subcellular localization patterns: (i) Endosomes; (ii) Lysosomes; (iii) Mitochondria; (iv) Peroxisomes; (v) Actin; (vi) Plasma Membrane; (vii) Microtubules; and (viii) Endoplasmic Reticulum. The data are based on those released by Dr. Nicholas Hamilton for his paper Statistical and visual differentiation of high throughput subcellular imaging, N. Hamilton, J. Wang, M.C. Kerr and R.D. Teasdale, BMC Bioinformatics 2009, 10:94. Select and implement a suitable active learning algorithm and apply it to the training data. Additionally, implement a random learner that selects random images in the training data. Using a budget of 2,500 calls to the oracle, compute and plot the test errors for each algorithm as a function of the number of calls to the oracle. Use the test data to compute the test errors. Repeat this for the easy and moderate data pools. If you are working on a team, or want extra credit, apply your algorithm to the difficult pool as well.
βΎοΈ CML - Continuous Machine Learning | CI/CD for ML
Cookiecutter template for a Python package.
Tutorials on Deep Learning
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Streamlit app demonstrating an image browser for the Udacity self-driving-car dataset with realtime object detection using YOLO.
Code examples for my article "Design Patterns in Scala"
https://docs.djangoproject.com/en/2.0/intro/tutorial01/
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Over 400 software engineering companies that are easy to apply to
Set of scripts to build a chatbot which will answer based on the FAQs supplied.
Python Stream Processing
MLSP - 2017
Distributed training framework for TensorFlow, Keras, and PyTorch.
A curated list of applied machine learning and data science notebooks and libraries across different industries.
Python client for Apache Kafka
Preparing for serious Kaggle competitions!
Turing Test's Solution for Home Depot Product Search Relevance Competition on Kaggle (https://www.kaggle.com/c/home-depot-product-search-relevance)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π 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. πππ
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 β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.