# Deep Learning

# Related articles

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

Categories: Data Engineering, Data Science, Learning | Tags: Deep Learning, AWS, Databricks, Deployment, Machine Learning, Azure, 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: Cloud, DevOps, On-premise, Operation, Schema, AI, Machine Learning, MLOps

“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, Docker, Jupyter, Linux, AI, 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, Node.js, React.js, Hadoop, Knox, Kubernetes

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, Node.js, Open API, Kubernetes, Neural Network

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: Spark, YARN, Deep Learning, GPU, Hadoop, 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