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TensorFlow 2.0 Tutorial : Optimizing Training Time Performance
TensorFlow 2.0 Tutorial : Optimizing Training Time Performance
This tutorial explores how you can improve training time performance of TensorFlow 2.0 models around tf.data, mixed precision or multi-GPU
Raphaël Meudec
Jan 30, 2020
Hands on hyperparameter tuning with Keras Tuner
Hands on hyperparameter tuning with Keras Tuner
This post will explain how to perform automatic hyperparameter tuning with Keras Tuner and Tensorflow 2.0 to boost accuracy on a computer…
Juliep
Jan 22, 2020
Optimize Response Time of your Machine Learning API in Production
Optimize Response Time of your Machine Learning API in Production
This article demonstrates how building a smarter API serving Deep Learning models minimizes the response time.
Yannick Wolff
Jan 13, 2020
The Best of AI: New Articles Published This Month (November 2019)
The Best of AI: New Articles Published This Month (November 2019)
10 data articles handpicked by the Sicara team, just for you
Jean
Dec 12, 2019
The Best of AI: New Articles Published This Month (October 2019)
The Best of AI: New Articles Published This Month (October 2019)
The Best of AI: New Articles Published This Month (October 2019)
Maria Romanenko
Nov 19, 2019
Deep Learning Memory Usage and Pytorch optimization tricks
Deep Learning Memory Usage and Pytorch optimization tricks
Mixed precision training and gradient checkpointing on a ResNet
Quentin Febvre
Oct 29, 2019
Face Detectors: Understand DSFD and the State-of-the-art Algorithms
Face Detectors: Understand DSFD and the State-of-the-art Algorithms
Such as Faster R-CNN and Single Shot Detector
Bastien Ponchon
Sep 30, 2019
Best Open Source Annotation Tools in Computer vision
Best Open Source Annotation Tools in Computer vision
A Top 5 labeling tools to create Computer Vision datasets
Laurent Montier
Sep 3, 2019
Interpretability of Deep Learning Models with Tensorflow 2.0
Interpretability of Deep Learning Models with Tensorflow 2.0
An introduction to interpretability methods to ease neural network training monitoring
Raphaël Meudec
Aug 28, 2019
Introducing tf-explain, Interpretability for TensorFlow 2.0
Introducing tf-explain, Interpretability for TensorFlow 2.0
A Tensorflow 2.0 library for deep learning model interpretability
Raphaël Meudec
Jul 31, 2019
Few-Shot Image Classification using Meta-Learning
Few-Shot Image Classification using Meta-Learning
You don’t always have enough images to train a deep neural network. Here is how you can teach your model to learn quickly from a few…
Etienne Bennequin
Jul 30, 2019
Image Registration: From SIFT to Deep Learning
Image Registration: From SIFT to Deep Learning
How the field has evolved from OpenCV to Neural Networks
Emna Kamoun
Jul 16, 2019
Basics in R Programming
Basics in R Programming
You are about to begin a project on R? Before you watch any tutorial, read these basic standards.
Alexandre Sapet
Apr 29, 2019
How To Build A Successful AI PoC
How To Build A Successful AI PoC
Turn Your Artificial Intelligence Ideas Into Working Software
Arnault Chazareix
Mar 29, 2019
Why Jupyter Is Not My Ideal notebook
Why Jupyter Is Not My Ideal notebook
From notebook prototyping to production the right way
Clément Walter
Feb 25, 2019
How Does Your Computer Generate Random Numbers?
How Does Your Computer Generate Random Numbers?
Everything you need to know about pseudo random generator.
Tanguy Marchand
Jan 28, 2019
How to Perform Fraud Detection with Personalized Page Rank
How to Perform Fraud Detection with Personalized Page Rank
Along with python package Networkx
Antoine Moreau
Jan 9, 2019
How to Write Perfect Python Command-line Interfaces
How to Write Perfect Python Command-line Interfaces
Yannick Wolff
Dec 18, 2018
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