Deep Learning
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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