# Deep Learning

# Related articles

## Adaltas Summit 2021, 2nd edition in corsica

Categories: Adaltas Summit 2021, Learning | Tags: Ansible, Blockchain, Deep Learning, Hadoop, Spark, Azure, Docker, Terraform, Kubernetes, Node.js

For its second edition, the whole Adaltas crew is gathering in Corsica for a whole week with 2 days dedicated to technology the 23rd and the 24th of september 2021. After a year and a half of sanitary…

By David WORMS

Sep 21, 2021

## Apache Liminal: when MLOps meets GitOps

Categories: Big Data, Containers Orchestration, Data Engineering, Data Science, Tech Radar | Tags: Data Engineering, Deep Learning, CI/CD, Data Science, Deployment, Docker, GitOps, Kubernetes, Machine Learning, MLOps, Open source, Python, TensorFlow

Apache Liminal is an open-source software which proposes a solution to deploy end-to-end Machine Learning pipelines. Indeed it permits to centralize all the steps needed to construct Machine Learning…

Mar 31, 2021

## TensorFlow Extended (TFX): the components and their functionalities

Categories: Big Data, Data Engineering, Data Science, Learning | Tags: Beam, Data Engineering, Deep Learning, Pipeline, CI/CD, Data Science, Deployment, Machine Learning, MLOps, Open source, Python, TensorFlow

Putting Machine Learning (ML) and Deep Learning (DL) models in production certainly is a difficult task. It has been recognized as more failure-prone and time consuming than the modeling itself, yet…

Mar 5, 2021

## Experiment tracking with MLflow on Databricks Community Edition

Categories: Data Engineering, Data Science, Learning | Tags: Deep Learning, Spark, Databricks, Delta Lake, Machine Learning, MLflow, Notebook, Python, Scikit-learn

Introduction to Databricks Community Edition and MLflow Every day the number of tools helping Data Scientists to build models faster increases. Consequently, the need to manage the results and the…

Sep 10, 2020

## MLflow tutorial: an open source Machine Learning (ML) platform

Categories: Data Engineering, Data Science, Learning | Tags: Deep Learning, AWS, Azure, Databricks, Deployment, Machine Learning, MLflow, MLOps, Python, Scikit-learn

Introduction and principles of MLflow With increasingly cheaper computing power and storage and at the same time increasing data collection in all walks of life, many companies integrated Data Science…

Mar 23, 2020

## Introduction to Ludwig and how to deploy a Deep Learning model via Flask

Categories: Data Science, Tech Radar | Tags: Deep Learning, Learning and tutorial, Ludwig Deep Learning Toolbox, Machine Learning, Python

Over the past decade, Machine Learning and deep learning models have proven to be very effective in performing a wide variety of tasks such as fraud detection, product recommendation, autonomous…

Mar 2, 2020

## Avoid Bottlenecks in distributed Deep Learning pipelines with Horovod

Categories: Data Science | Tags: Deep Learning, GPU, Horovod, Keras, TensorFlow

The Deep Learning training process can be greatly speed up using a cluster of GPUs. When dealing with huge amounts of data, distributed computing quickly becomes a challenge. A common obstacle which…

By Grégor JOUET

Nov 15, 2019

## Machine Learning model deployment

Categories: Big Data, Data Engineering, Data Science, DevOps & SRE | Tags: DevOps, Operation, AI, Cloud, Machine Learning, MLOps, On-premises, Schema

“Enterprise Machine Learning requires looking at the big picture […] from a data engineering and a data platform perspective,” lectured Justin Norman during the talk on the deployment of Machine…

Sep 30, 2019

## TensorFlow installation on Docker

Categories: Containers Orchestration, Data Science, Learning | Tags: CPU, Deep Learning, Jupyter, Linux, AI, Docker, TensorFlow

TensorFlow is an Open Source software from Google for numerical computation using a graph representation: Vertex (nodes) represent mathematical operations Edges represent N-dimensional data array…

Aug 5, 2019

## Applying Deep Reinforcement Learning to Poker

Categories: Data Science | Tags: Algorithm, Deep Learning, Gaming, Q-learning, Machine Learning, Neural Network, Python

We will cover the subject of Deep Reinforcement Learning, more specifically the Deep Q Learning algorithm introduced by DeepMind, and then we’ll apply a version of this algorithm to the game of Poker…

Jan 9, 2019

## One week to discuss technology in a Moroccan riad

Categories: Adaltas Summit 2018, Learning | Tags: Flink, CDSW, Deep Learning, Gatsby, React.js, Hadoop, Knox, Data Science, Kubernetes, Node.js

Adaltas organise the year its first conference between the 22 and 26 of October. On the agenda of these 5 days of conference: discuss technology in one of the most beautiful riad of Marrakech. Mix the…

By David WORMS

Oct 11, 2018

## Nvidia and AI on the edge

Categories: Data Science | Tags: Caffe, Deep Learning, Edge computing, GPU, NVIDIA, AI, Keras, PyTorch, TensorFlow

In the last four years, corporations have been investing a lot in AI and particularly in Deep Learning and Edge Computing. While the theory has taken huge steps forward and new algorithms are invented…

By Yliess HATI

Oct 10, 2018

## Lando: Deep Learning used to summarize conversations

Categories: Data Science, Learning | Tags: Deep Learning, Micro Services, Open API, Kubernetes, Neural Network, Node.js

Lando is an application to summarize conversations using Speech To Text to translate the written record of a meeting into text and Deep Learning technics to summarize contents. It allows users to…

By Yliess HATI

Sep 18, 2018

## Deep learning on YARN: running Tensorflow and friends on Hadoop cluster

Categories: Data Science | Tags: YARN, Deep Learning, GPU, Hadoop, Spark, Spark MLlib, PyTorch, TensorFlow, XGBoost, MXNet

With the arrival of Hadoop 3, YARN offer more flexibility in resource management. It is now possible to perform Deep Learning analysis on GPUs with specific development environments, leveraging…

Jul 24, 2018