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Julien Herzen
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Published in Unit8 - Big Data & AI

·May 5

Transfer Learning for Time Series Forecasting

In this article, we will see how transfer learning can be applied to time series forecasting, and how forecasting models can be trained once on a diverse time series dataset and used later on to obtain forecasts on different datasets without training. We will use the open-source Darts library to…

Timeseries

12 min read

Transfer Learning for Time Series Forecasting
Transfer Learning for Time Series Forecasting

Published in Unit8 - Big Data & AI

·Aug 13, 2021

Time Series Forecasting Using Past and Future External Data with Darts

Building models that are able to capture external data is often a key aspect of time series forecasting projects. For instance: Recently-observed activity on an e-commerce website can help predict future sales. Observed rainfalls and known weather forecasts can help to predict hydro and solar electricity production. Making the model…

Timeseries

9 min read

Time Series Forecasting Using Past and Future External Data with Darts
Time Series Forecasting Using Past and Future External Data with Darts

Published in Unit8 - Big Data & AI

·Mar 18, 2021

Better, Cheaper, Faster: How Artificial Intelligence Is Changing the Way of Discovering New Chemicals

Advanced analytics and artificial intelligence (AI) are becoming increasingly important for the chemical industries. In the past, chemical companies were often relying on analytics tools that now appear fairly basic for making critical decisions within research and development (R&D), manufacturing, creation, supply chain and sales. Today, the ability of a…

Chemistry

5 min read

Better, Cheaper, Faster: How Artificial Intelligence Is Changing the Way of Discovering New…
Better, Cheaper, Faster: How Artificial Intelligence Is Changing the Way of Discovering New…

Published in Unit8 - Big Data & AI

·Feb 15, 2021

Training Forecasting Models on Multiple Time Series with Darts

Any quantity varying over time can be represented as a time series: sales numbers, rainfalls, stock prices, CO2 emissions, Internet clicks, network traffic, etc. Time series forecasting — the ability to predict the future evolution of time series— is thus a key capability in many domains where anticipation is important…

Timeseries

11 min read

Training Forecasting Models on Multiple Time Series with Darts
Training Forecasting Models on Multiple Time Series with Darts

Published in Unit8 - Big Data & AI

·Jun 29, 2020

Darts: Time Series Made Easy in Python

Time series simply represent data points over time. They are thus everywhere in nature and in business: temperatures, heartbeats, births, population dynamics, internet traffic, stocks, inventories, sales, orders, factory production — you name it. In countless cases, efficient processing and forecasting of time series has the potential to provide decisive…

Timeseries

7 min read

Darts: Time Series Made Easy in Python
Darts: Time Series Made Easy in Python

Published in Unit8 - Big Data & AI

·Feb 15, 2020

Routing Traveling Salesmen on Random Graphs Using Reinforcement Learning, in PyTorch

This is joint work with Vincent Stettler. The complete code is available here. In this post, we will explore a fascinating emerging topic, which is that of using reinforcement learning to solve combinatorial optimization problems on graphs. We will see how this can be done concretely for finding solutions to…

Machine Learning

15 min read

Routing Traveling Salesmen on Random Graphs using Reinforcement Learning, in PyTorch
Routing Traveling Salesmen on Random Graphs using Reinforcement Learning, in PyTorch

Published in Unit8 - Big Data & AI

·Nov 13, 2018

Computing the Jacobian matrix of a neural network in Python

In general, a neural network is a multivariate, vector-valued function looking like this:

Machine Learning

8 min read

Computing the Jacobian matrix of a neural network in Python
Computing the Jacobian matrix of a neural network in Python
Julien Herzen

Julien Herzen

Lead data scientist @ Unit8 www.hrzn.ch

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