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Archives for October 2020

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Build a fully production ready machine learning app with Python Django, React, and Docker towardsdatascience.com

Published October 1, 2020 under Web Development

Build a fully production ready machine learning app with Python Django, React, and Docker

A complete, step by step guide to building a production-grade machine learning app with Django, PostgreSQL, React, Redux and Docker

Machine Learning, ReactJS

Automate Excel with Python Tutorial youtube.com

Published October 1, 2020 under Python

Excel, Pandas

Introducing PyTorch Forecasting towardsdatascience.com

Published October 1, 2020 under Data Science

Introducing PyTorch Forecasting

Forecasting time series is important in many contexts and highly relevant to machine learning practitioners. Take, for example, demand forecasting from which many use cases derive. Almost every manufacturer would benefit from better understanding demand for their products in order to optimise produced quantities. Underproduce and you will lose revenues, overproduce and you will be forced to sell excess produce at a discount. Very related is pricing, which is essentially a demand forecast with a specific focus on price elasticity. Pricing is relevant to virtually all companies.

Forecasting, PyTorch

A Low-Cost Introduction to Machine Learning Training on Microsoft Azure nag.com

Published October 1, 2020 under Machine Learning

This tutorial demonstrates porting an existing machine learning model to a virtual machine on the Microsoft Azure cloud platform. We will train a small movie recommendation model using a single GPU to give personalised recommendations. The total cost of performing this training should be no more than $5 using any of the single GPU instances currently available on Azure.

Azure, NAG

How to build a custom production-ready Deep Learning Training loop in Tensorflow from scratch theaisummer.com

Published October 1, 2020 under Data Science

How to build a custom production-ready Deep Learning Training loop in Tensorflow from scratch

Training is without a doubt the most important part of developing a machine learning application. It’s when you start realizing whether or not your model is worth it, how your hyperparameters should look like and what do you need to change in your architecture. In general, most machine learning engineers spend quite some time on training, experimenting with different models, tuning their architecture and discovering the best metrics and losses for their problem.

Deep Learning, TensorFlow

Scientific Computing in Python: Introduction to NumPy and Matplotlib sebastianraschka.com

Published October 1, 2020 under Data Science

Scientific Computing in Python: Introduction to NumPy and Matplotlib

Numerical Methods, Numpy

Making Concurrent HTTP requests with Python AsyncIO laac.dev

Published October 1, 2020 under Web Development

Making Concurrent HTTP requests with Python AsyncIO

We’ll demonstrate the usage of concurrent HTTP requests by fetching prices for stock tickers. The only third party package we’ll use is httpx. Httpx is very similar to the popular requests package, but httpx supports asyncio.

Investing, Trading

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