Machine Learning Tutorial: The Naive Bayes Text Classifier


In this tutorial we will discuss about Naive Bayes text classifier. Naive Bayes is one of the simplest classifiers that one can use because of the simple mathematics that are involved and due to the fact that it is easy to code with every standard programming language including PHP, C#, JAVA etc.

Fitting Gaussian Process Models in Python


Written by Chris Fonnesbeck, Assistant Professor of Biostatistics, Vanderbilt University Medical Center. You can view, fork, and play with this project on the Domino data science platform.

Avoiding Look Ahead Bias in Time Series Modelling


Any time series classification or regression forecasting involves the Y prediction at't n' given the X and Y information available till time T. Obviously no data scientist or statistician can deploy the system without back testing and validating the performance of model in history. Using the future actual information in training data which could be termed as "Look Ahead Bias" is probably the gravest mistake a data scientist can make. Even the sentence "we cannot make use future data in training" sounds too obvious and simple in theory, anyone unknowingly can add look ahead bias in complex forecasting problems.

Faiss: A library for efficient similarity search


This month, we released Facebook AI Similarity Search (Faiss), a library that allows us to quickly search for multimedia documents that are similar to each other -- a challenge where traditional query search engines fall short. We've built nearest-neighbor search implementations for billion-scale data sets that are some 8.5x faster than the previous reported state-of-the-art, along with the fastest k-selection algorithm on the GPU known in the literature. This lets us break some records, including the first k-nearest-neighbor graph constructed on 1 billion high-dimensional vectors.

Supercharge healthcare with artificial intelligence


Pattern-recognition algorithms can transform horses into zebras; winter scenes can become summer; artificial intelligence algorithms can generate art; robot radiologists can analyze your X-rays with remarkable precision.

Android Things and Machine Learning


Android Things allows you to make amazing IoT devices with simple code, but one of the things that can make a device extraordinary is machine learning. While there are a few services available online that will allow you to upload data and will return results, being able to use machine learning locally and offline can be incredibly useful.

10 Essential Algorithms For Machine Learning Engineers


It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before.

ml4seti SETI Institute


The SETI Institute of Mountain View is inviting all citizen data scientists and technologists to join us as collaborators in our mission to find intelligent radio signals from beyond our solar system. We are issuing a worldwide, public code challenge and accompanying hackathon for the purpose of expanding our radio-telescope signal classification tools using the latest developments available in machine- and deep-learning.

AI turns children’s books illustrations into nightmares

Daily Mail

Researchers have seen hundreds of children's books through the eyes of an AI – and it was a nightmare.

40 Interview Questions asked at Startups in Machine Learning / Data Science


This article was posted by Manish Saraswat on Analytics Vidhya. Manish who works in marketing and Data Science at Analytics Vidhya believes that education can change this world. R, Data Science and Machine Learning keep him busy.