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Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
A template and short tutorial on nextflow for computational statisticians
We are building an open database of COVID-19 cases with chest X-ray or CT images.
A Tutorial for Serving Tensorflow Models using Kubernetes
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
The Go Cloud Development Kit (Go CDK): A library and tools for open cloud development in Go.
General code to convert a trained keras model into an inference tensorflow model
A clear, concise, simple yet powerful and efficient API for deep learning.
Fletcher: A framework to integrate FPGA accelerators with Apache Arrow
For the latest version of boto, see https://github.com/boto/boto3 -- Python interface to Amazon Web Services
Automate your OKCupid Activity. This is an API Wrapper for OkCupid App, allowing you to automate processes and collect data for further analysis
Subpar is a utility for creating self-contained python executables. It is designed to work well with Bazel.
Code for In silico labeling: Predicting fluorescent labels in unlabeled images
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
Machine Learning Toolkit for Kubernetes
Source-to-Source Debuggable Derivatives in Pure Python
A new programming model for asynchronous and distributed programming.
Programming Models for Distributed Computation, analyses & minutes
[deprecated] Jupyter CoLaboratory, goto google colab now
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
The easiest way to use git. On any platform. Anywhere.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"