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Machine Learning
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museum watching

Few-Shot Image Classification with Meta-Learning

Here is how you can teach your model to learn quickly from a few examples.

Grad CAM Method (Original Photo by Kelly Lund on Unsplash)

Introducing tf-explain, Interpretability for TensorFlow 2.0

A Tensorflow 2.0 library for deep learning model interpretability.

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Determine Your Network Hyper-parameters With Bayesian Optimization

Why and how Bayesian Optimization can be used for hyper-parameters tuning

annotation tools

Best Open Source Annotation Tools for Computer Vision

A Top 5 labeling tools to create Computer Vision datasets.

Grad CAM method on ‘deer’ ImageNet class (Original photo by Asa Rodger on Unsplash)

Interpretability of Deep Learning Models with Tensorflow 2.0

An introduction to interpretability methods to ease neural network training monitoring.

museum watching

Few-Shot Image Classification with Meta-Learning

Here is how you can teach your model to learn quickly from a few examples.

bridge

Image Registration: From SIFT to Deep Learning

How the field has evolved from OpenCV to Neural Networks.

rboy

Basics in R Programming

You are about to begin a project on R? Before you watch any tutorial, read these basic standards.

how to build a successful ai poc

How To Build A Successful AI PoC

Turn Your Artificial Intelligence Ideas Into Working Software

Edge detection, tutorial, knowledge

Edge Detection in Opencv 4.0, A 15 Minutes Tutorial

This tutorial will teach you, with examples, two OpenCV techniques in python to deal with edge detection.

TensorFlow, AI, Docker, GPU

Set up TensorFlow with Docker + GPU in Minutes

Why Docker is the best platform to use Tensorflow with a GPU.

Gaussian Distribution With Bean Machine

Naive Bayes Classification With Sklearn

This tutorial details Naive Bayes classifier algorithm, its principle, pros & cons, and provides an example using the Sklearn python Library.

dices

How Does Your Computer Generate Random Numbers?

What you should know about numpy and pseudo random number generators (PRNG).

Spark with Jupyter

Get Started with PySpark and Jupyter Notebook in 3 Minutes

Spark is a fast and powerful framework.

Learn to Test Your Pyspark Project with Pytest — example-based Tutorial

In this tutorial, I will explain how to get started with test writing for your Spark project.

thief

How to Perform Fraud Detection with Personalized Page Rank

This article shows how to perform fraud detection with Graph Analysis.

This year NeurIPS is returning to Montreal.

NeurIPS (prev. NIPS) Papers Selection

My favorite research articles from NeurIPS (previously NIPS) 2018.

fig. 1: Screenshot of my React app using the neural networks computed here.

Introduction to Deep Q-learning with SynapticJS & ConvNetJS

An application to the Connect 4 game.

named entity recognition

Python: How to Train your Own Model with NLTK and Stanford NER Tagger? (for English, French, German…)

This guide shows how to use NER tagging for English and non-English languages with NLTK and Standford NER tagger (Python). You can also use it to improve the Stanford NER Tagger.

blurry street

GAN with Keras: Application to Image Deblurring

A Generative Adversarial Networks tutorial applied to Image Deblurring with the Keras library.

Speedup Your R Code with RStudio in AWS

What if AWS could save you days without changing your usual workflow?

TensorFlow, AI, Docker, GPU

Set up TensorFlow with Docker + GPU in Minutes

Why Docker is the best platform to use Tensorflow with a GPU.

graph

Keras Tutorial: Content Based Image Retrieval Using a Denoising Autoencoder

How to find similar images thanks to Convolutional Denoising Autoencoder.

man ready to sprint

Surgical Time Tracking in Python

How to profile your python code to improve performance

dino

Was Darwin a Great Computer Scientist?

How evolution taught us the “genetic algorithm”.

weird brain

Fast Custom KNN in Sklearn Using Cython

Let’s dive into how you can implement a fast custom KNN in Scikit-learn.