Machine Learning

I am developing a small project to detect anomalies that indicate malicious traffic on networks.The idea is to capture traffic in real time with software made in Go using the Google gopacket library (https://github.com/google/gopacket).After that, I will use the Isolation Forest machine learning algorithm to detect anomalies (outliers) in the traffic that is captured in the … [Read more...] about Detecting traffic anomalies on networks with ML and Go

Photo by fabio on UnsplashThe Pillars of Data Science ExpertiseWhile data scientists often come from many different educational and work experience backgrounds, most should be strong in, or in an ideal case be experts in four fundamental areas. In no particular order of priority or importance, these are:Business/Domain Mathematics (includes statistics and probability) Computer … [Read more...] about What is data science used for?

In the real world, datasets are dirty. This data must be processed before data analysis. Data preprocessing is one of the most important stages of data analysis. The most time-consuming step for data scientists is data preprocessing. Pandas is one of the most important libraries of Python. In this post, I will talk about the Pandas library.Photo by Luke Chesser on … [Read more...] about INTRODUCTION TO THE PANDAS LIBRARY

After “part I” which gave an introduction on how to import, process, and analyze a tandem mass spectra dataset using Python and matchms, “part II” will add Spec2Vec to the game, a machine learning tool to assess spectrum similarities.[last edit: 17/02/2021]In part I of this tutorial, matchms, a Python library to import, process, and compare tandem mass spectrometry data was … [Read more...] about Build a mass spectrometry analysis pipeline in Python using matchms — part II: Spec2Vec

The models can have many hyperparameters and finding the best combination of the parameter using grid search methods.Grid search is a technique for tuning hyperparameter that may facilitate build a model and evaluate a model for every combination of algorithms parameters per grid.We might use 10 fold cross-validation to search the best value for that tuning hyperparameter. … [Read more...] about Hyperparameter Tuning of Decision Tree Classifier Using GridSearchCV

Have you ever thought how computers recognize objects? It is completely different from the way humans identify objects. The Computer understands an image as an array of numbers because they only interact with numbers. Every object has a specific pattern and computer will follow that pattern to identify an object in an image.A convolutional neural network (CNN) is a neural … [Read more...] about Introduction to Convolutional Neural Networks

When we started building our services business, Neuralastic, Inc, we were startled to see that in spite of such fanfare, medium-sized firms had little or no AI capabilities. As we progressed, it dawned on us that the primary reason for the lack of adoption was the lack of data.Even now, most firms don’t see their daily business data as a source of insights, beyond excel charts. … [Read more...] about Future of AI: No data, No Problem

L’univers de la Data est très vaste, et couvre des domaines de compétences variés.Pourtant que l’on soit Data Scientist, Data Analyst, ou ML Ops, il est intéressant de se tenir informé des nouveautés touchant de près ou de loin notre spécialité.Chez SFEIR, entre passionnés de Data, nous avons souhaité mettre notre veille en commun, afin de partager nos sources et centres … [Read more...] about Data Log #1, revue de presse Data

Figure 1. Sample results of SinGAN.SinGAN is a novel unconditional* generative model that is trained using a single image. Traditionally, GANs have been trained on class-specific datasets and capture common features among images of the same class. SinGAN, on the other hand, learns from the overlapping patches at multiple scales of a particular image and learns its internal … [Read more...] about A In-Depth Look at SinGAN

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.The process of learning begins with observations or data, such as … [Read more...] about An Introduction to Machine Learning