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Machine Learning

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Great Reads

by Thomas Weller
Demonstrates how to run Python scripts from C#
by Andy Allinger
Add features to k-means for missing data, mixed data, and choosing the number of clusters
by Dmitriy Gakh
The perspectives of creating bots that write programs with two simple examples.
by Andrew Kirillov
The article demonstrates usage of ANNT library for creating convolutional ANNs and applying them to image classification tasks.

Latest Articles

by Michael Chourdakis
An introduction to machine learning with working C++ code that trains a linear regression model.
by Nicolas DESCARTES
How to implement neural networks in C#?
by Nicolas DESCARTES
How to implement logistic regression in ML.NET?

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Machine Learning 

N 18 Apr 2024 by Michael Chourdakis
An introduction to machine learning with working C++ code that trains a linear regression model.
12 Jan 2024 by Nicolas DESCARTES
How to implement logistic regression in ML.NET?
8 Jan 2024 by Nicolas DESCARTES
What clustering algorithm should be selected for the clustering task?
11 Dec 2023 by Nicolas DESCARTES
What is naive Bayes and how to implement it?
8 Nov 2023 by Chris Maunder
Dive into the world of machine learning and explore how it empowers businesses to extract valuable insights from vast amounts of data. Discover practical techniques and tools for successful implementation.
25 Oct 2023 by Cloud Native Apps Team
In this four-part series, you’ll learn how to create an Intelligent App with Azure Container Apps. In this fourth and final part, you’ll explore how to integrate a custom model into your Intelligent Apps, enhancing the application’s features with specialized AI.
24 Oct 2023 by Cloud Native Apps Team
In this four-part series, you’ll learn how to create an Intelligent App with Azure Container Apps. In this third part, you’ll explore how to level up your Intelligent Apps by training a custom model using your own dataset.
30 Sep 2023 by Ujwal Watgule
The Cheetah Optimizer is a nature-inspired metaheuristic algorithm designed to tackle complex optimization problems across multiple dimensions.
22 Sep 2023 by Cloud Native Apps Team
Check out this article of our series on intelligent apps to learn best practices for transitioning your on-premises or IaaS solutions to intelligent apps.
9 Sep 2023 by chlohee
Machine Learning. What languages come to mind? R? Python? Matlab? Bet you didn't think Visual Basic.
21 Aug 2023 by Jin Choi, PhD
A layman's description of how Kalman Filters work, and sample code that shows how to use it to forecast stock market volatilities
15 Aug 2023 by Ujwal Watgule
Credit card fraud detection is an important application of machine learning techniques.
14 Jun 2023 by pi19404
Supervised ML algorithm for multi-class classification
7 Jun 2023 by Andy Allinger
Add features to k-means for missing data, mixed data, and choosing the number of clusters
22 May 2023 by Grasshopper.iics, Abhishek Nandy, Moumita Das
Industrial IoT time series data collection with GE Predix time series ingestion and data streaming
21 May 2023 by Shun Huang
Basics of ML and Perception learning algorithm
13 May 2023 by Dmitrii Nemtsov
A way to build a finite-state machine identifying predefined sequences in a stream of characters
10 Jun 2022 by Gaston Verelst
How to use F# to implement algorithms such of k-means
8 Jun 2022 by Ganesan Senthilvel
An interesting article on Artificial Intelligence Chat Ro(Bot) application development
20 May 2022 by Sau002
How to create C# applications using TensorFlowSharp
2 May 2022 by KristianEkman
How to build an AI which plays Backgammon
15 Dec 2021 by asiwel
Bezier Curve Classification Training And Validation Models Using ALGLIB
7 Dec 2021 by Mahsa Hassankashi
Deep learning convolutional neural network by tensorflow python, complete and easy understanding
28 Jul 2021 by Abdulkader Helwan
In this article, we show you how to set up an Android Studio environment that is suitable for loading and running our .tflite model.
22 Jul 2021 by MehreenTahir
In this article we learn about how Azure Synapse Analytics and Azure Machine Learning help analyze data without extensive coding and ML experience.
19 Jul 2021 by Shweta Lodha
This article walks you through the steps required to create a custom ML model, train it and then use the same model to analyze the sales receipt.
9 Jul 2021 by Shweta Lodha
Ways to extract information from sales receipt and detailed demonstration of how to use pre-built ML models
25 May 2021 by Jarek Szczegielniak
In this article, we publish our NLP API service to Azure using Azure Container Instances.
21 May 2021 by Jarek Szczegielniak
In this article we use Visual Studio Code to edit and debug our increasingly complex code running inside a Docker container.
20 May 2021 by Jarek Szczegielniak
In this article, we’ll modify our code to expose the same logic via a Rest API service.
19 May 2021 by Jarek Szczegielniak
In this article we run an inference model for NLP using models persisted on a Docker volume.
18 May 2021 by Jarek Szczegielniak
In this article we run inference on sample images with TensorFlow using a containerized Object Detection API environment.
11 May 2021 by Sergio Virahonda
In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
10 May 2021 by Sergio Virahonda
In this article we build the model API to support the prediction service.
7 May 2021 by Sergio Virahonda
In this article, we develop a model unit testing container.
6 May 2021 by Sergio Virahonda
In this article, we’ll deep-dive into the Continuous Training code.
5 May 2021 by Sergio Virahonda
In this article, we’ll implement automatic training.
4 May 2021 by Sergio Virahonda
In this article, we set up a cloud environment for this project.
3 May 2021 by Sergio Virahonda
In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
29 Apr 2021 by Jarek Szczegielniak
In this article we go back to the Intel/AMD CPUs. This time, we will speed up our calculations using a GPU.
27 Apr 2021 by Jarek Szczegielniak
In this article, we’ll adapt our image for Raspberry Pi with an ARM processor.
27 Apr 2021 by Jarek Szczegielniak
In this article, we’ll create a container to run a CPU inference on the trained model.
26 Apr 2021 by Jarek Szczegielniak
In this article, we’ll start applying our basic Docker knowledge while creating and running containers in the various MLng scenarios.
23 Apr 2021 by Jarek Szczegielniak
In this article – the first one of the series – we’ll go over some Docker basics as they apply to ML applications.
14 Apr 2021 by Martin_Rupp
In this article we introduce the main theoretical concepts required for building an ML-based translator.
1 Apr 2021 by Sergio Virahonda
In this article I’ll show you how to train your deep fake models in the cloud with some help from Docker.
9 Nov 2020 by Arnaldo P. Castaño
To end off this series, we will present the alternative of adapting a pre-trained CNN to the coin recognition problem we have been examining all along.
4 Nov 2020 by Arnaldo P. Castaño
In this article we will go over the basics of supervised machine learning and what the training and verification phases consist of.
2 Oct 2020 by philoxenic
In article in this series we will look at even deeper customisation: editing the XML-based model of the figure and then training the result.
1 Oct 2020 by philoxenic
In this article we will try to train our agent to run backwards instead of forwards.
30 Sep 2020 by philoxenic
In this article we will adapt our code to train the Humanoid environment using a different algorithm: Soft Actor-Critic (SAC).
29 Sep 2020 by philoxenic
In this article in the series we start to focus on one particular, more complex environment that PyBullet makes available: Humanoid, in which we must train a human-like agent to walk on two legs.
28 Sep 2020 by philoxenic
In this article, we look at two of the simpler locomotion environments that PyBullet makes available and train agents to solve them.
25 Sep 2020 by philoxenic
In this article, we set up with the Bullet physics simulator as a basis for doing some reinforcement learning in continuous control environments.
4 Sep 2020 by Keith Pijanowski
In this article I provide a brief overview of Keras for those looking for a deep learning framework for building and training neural networks
3 Sep 2020 by Keith Pijanowski
This article is the first in a series of seven articles in which we will explore the value of ONNX with respect to three popular frameworks and three popular programming languages.
1 Sep 2020 by Jarek Szczegielniak
In this article we can proceed to train our custom hot dog detection model using Apple’s Create ML.
31 Aug 2020 by Jarek Szczegielniak
In this article we’ll start data preparation for this new, custom model, to be later trained using the Create ML framework.
28 Aug 2020 by Jarek Szczegielniak
Having converted a ResNet model to the Core ML format in the previous article, in this article we’ll now use it in a simple iOS application.
27 Aug 2020 by Jarek Szczegielniak
In this article we'll convert a ResNet model to the Core ML format.
26 Aug 2020 by Jarek Szczegielniak
In this article we prepare our development environment.
7 Aug 2020 by Arnaldo P. Castaño
In this article we focus on the Text-to-Speech with the use of Deep Learning.
6 Aug 2020 by Arnaldo P. Castaño
In this article we’ll adapt the VGG16 model.
5 Aug 2020 by Arnaldo P. Castaño
In this article we’ll put together our CNN and train it for face recognition.
4 Aug 2020 by Arnaldo P. Castaño
In this article, we’ll talk about preparing a dataset for feeding the correct data to a CNN.
31 Jul 2020 by Arnaldo P. Castaño
In this article, we go over the steps to detect faces in an image.
23 Jul 2020 by Habibur Rony
Basics of the rule-based chatbot, machine-learning chatbot and AI chatbot.
15 Jul 2020 by Raphael Mun
In this article, we will take photos of different hand gestures via webcam and use transfer learning on a pre-trained MobileNet model to build a computer vision AI that can recognize the various gestures in real time.
14 Jul 2020 by Raphael Mun
In this article, we are going to use BodyPix, a body part detection and segmentation library, to try and remove the training step of the face touch detection.
13 Jul 2020 by Raphael Mun
In this article, we are going to use all that we’ve learned so far with computer vision in TensorFlow.js to try building a version of this app ourselves.
10 Jul 2020 by Raphael Mun
In this article we will build a Fluffy Animal Detector, where I will show you a way to leverage a pre-trained Convolutional Neural Network (CNN) model like MobileNet.
9 Jul 2020 by Raphael Mun
In this article, we’ll dive into computer vision running right within a web browser.
8 Jul 2020 by Raphael Mun
In this article, I will show you how quickly and easily set up and use TensorFlow.js to train a neural network to make predictions from data points.
6 Jul 2020 by philoxenic
In this final article in this series, we will look at slightly more advanced topics: minimizing the "jitter" of our Breakout-playing agent, as well as performing grid searches for hyperparameters.
3 Jul 2020 by philoxenic
In this article, we will see how we can improve by approaching the RAM in a slightly different way.
2 Jul 2020 by philoxenic
In this article we will learn from the contents of the game’s RAM instead of the pixels.
30 Jun 2020 by philoxenic
In this article, we will see how you can use a different learning algorithm (plus more cores and a GPU) to train much faster on the mountain car environment.
29 Jun 2020 by philoxenic
In this article, we start to look at the OpenAI Gym environment and the Atari game Breakout.
26 Jun 2020 by philoxenic
In this article, we will see what’s going on behind the scenes and what options are available for changing the reinforcement learning.
25 Jun 2020 by philoxenic
In this article, you will be up and running, and will have done your first piece of reinforcement learning.
23 Jun 2020 by Thomas Daniels
In this article we take a quick look at NumPy and TensorFlow also do a short overview of the scikit-learn library.
22 Jun 2020 by Thomas Daniels
In this article, let’s dive into Keras, a high-level library for neural networks.
19 Jun 2020 by Thomas Daniels
In this article we take a look at what you can do with the Natural Language Toolkit (NLTK).
18 Jun 2020 by Thomas Daniels
In this article let's get started hands-on with OpenCV.
17 Jun 2020 by Thomas Daniels
In this article we can take a look at what libraries are available to work on AI and ML tasks.
16 Jun 2020 by Thomas Daniels
In this article we go a bit further with generators and classes.
15 Jun 2020 by Thomas Daniels
Now that you know some of the basics of Python we can go a bit deeper, with the lists and tuples data structures and see how to work with them.
12 Jun 2020 by Thomas Daniels
This article provides some tips for experienced programmers to get up to speed with the basics of Python.
11 Jun 2020 by Glenn Prince
This article gives you a good starting point for your own object detection projects.
10 Jun 2020 by Glenn Prince
In this article, we begin the process of creating a custom object detection model.
9 Jun 2020 by Glenn Prince
In this article, we train our own custom model to detect if people are wearing hardhats.
8 Jun 2020 by Glenn Prince
In this article, we'll have a look at some of the pretrained models we can use in ImageAI to start detecting people in images.
6 Jun 2020 by Alaa Ben Fatma
A visual scripting environment for R & data science
5 Jun 2020 by Glenn Prince
In this article, we create an object detection model.
4 Jun 2020 by Glenn Prince
In this article, we'll set up everything we need to build a hardhat detector with OpenCV.
29 May 2020 by Jayson DeLancey
This article is the third in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this article, we'll look at techniques you can use to start doing the actual NLP analysis.
29 May 2020 by Glenn Prince
This article is the first in the Data Cleaning with Python and Pandas series that helps working developers get up to speed on data science tools and techniques.