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Machine Learning
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convolutional layer and convolution kernel

About Convolutional Layer and Convolution Kernel

A story of Convnet in machine learning from the perspective of kernel sizes.


Hands on hyperparameter tuning with Keras Tuner

Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%

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How to Train and Deploy Custom Models with Amazon SageMaker - Part 1

Training a Computer Vision Model on AWS using Tensorflow, Docker and Amazon SageMaker.


3 Reasons Why We Are Far From Achieving Artificial General Intelligence

How far we are from achieving Artificial General Intelligence? We answer this through the study of three limitations of current machine learning.

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.

Deep Learning Memory Usage and Pytorch Optimization Tricks

Understanding memory usage in deep learning models training

Determine Your Network Hyperparameters With Bayesian Optimization

Why and how Bayesian Optimization can be used for hyperparameters tuning


TensorFlow 2.0 Tutorial : Optimizing Training Time Performance

Tricks to improve TensorFlow training time with tf.data pipeline optimizations, mixed precision training and multi-GPU strategies

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.

weird brain

Fast Custom KNN in Sklearn Using Cython

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

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?

This guide shows how to use NER tagging with NLTK and Standford NER tagger (Python).

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.

TensorFlow, AI, Docker, GPU

Set up TensorFlow with Docker + GPU in Minutes

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

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.


Was Darwin a Great Computer Scientist?

How evolution taught us the “genetic algorithm”.

how to build a successful ai poc

How To Build A Successful AI PoC

Turn Your Artificial Intelligence Ideas Into Working Software

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.


How Does Your Computer Generate Random Numbers?

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


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.

man ready to sprint

Surgical Time Tracking in Python

How to profile your python code to improve performance