Scala or Scalable language is an extension of Java language which runs on Java Virtual Machine (JVM). It is one of the de facto languages when it comes to playing practically with Big Data. This statically-typed language serves as an important tool for the data scientists because it supports both anonymous functions as well as higher-order functions. In this article, we list down 10 Scala Libraries for a data science enthusiast. Breeze is a set of libraries for machine learning and numerical computing and is a part of ScalaNLP umbrella project.

Machine learning is everywhere these days, from the photos on your phone to the filtering system in your email Inbox. Machine learning has become one of the most key components of the future. With the trend of the internet becoming more personalized, machine learning has become more important now than ever. Even big companies like Amazon use machine learning algorithms to provide you with recommendations based on your interests. Around a decade ago, the main purpose of the internet was to provide you with information -- one keyword would generate results from around the globe on that particular keyword.

In this post, we shall discuss the leading data science and machine learning projects at GitHub. What's the best stage for facilitating your code, working together with colleagues, and furthermore that goes about as an online resume to grandstand your coding abilities? Ask any data scientist and they'll point you towards GitHub. It has been a really progressive platform lately and has changed the scene of how we host and even do coding. Here are some of the best data science and machines learning projects at GitHub.

We've been over this a bunch of times, but it's clear enough to say that machine learning is one of the hottest skills in tech right now. Earlier this year, Stack Overflow published results from a massive developer survey that ML specialists were second only to DevOps specialists in terms of pay. Machine learning is experiencing something of a boom time, but open source can often be a bit confusing for newcomers. So, today we're taking a closer look at the top five open source projects on GitHub to see how the field is developing and see where your help could be used. After all, open source succeeds thanks to collaboration between developers and programmers all around the world!

Open source software is an important piece of the data science puzzle. According to the most recent KDnuggets data science software poll results, 73% of data scientists used free software in the previous 12 months. While there are many sources of such tools on the internet, Github has become a de facto clearinghouse for all types of open source software, including tools used in the data science community. The importance, and central position, of machine learning to the field of data science does not need to be pointed out. The following is an overview of the top 10 machine learning projects on Github.* The top project is, unsurprisingly, the go-to machine learning library for Pythonistas the world over, from industry to academia.

Use in transforming unstructured data into structured especially in social media monitoring, business intelligence, content recommendations, financial trading and targeted advertising. A live mashup that consumes Alina demonstrates the API's ability to use genetic algorithms and artificial neural networks to analyze historical Bitcoin price fluctuations to predict and automate future trading. Amazon Machine Learning: To find patterns in data. Example uses of this API are applications for fraud detection, forecasting demand, targeted marketing, and click prediction BigML: BigML is a service for cloud-hosted machine learning and data analysis. Users can set up a data source, create a dataset, create a model from the dataset, and then make predictions based on the data.

PredictionIO is an open source machine learning server, and is a recent addition to the Apache family.

When millions of people across the world tuned in to watch DeepMind's machine beat the human Go world champion Lee Sedol, they also witnessed a historic victory for open-source. DeepMind used a scientific computing framework called Torch extensively in the development and execution of AlphaGo's neural networks. Torch was first released back in 2002 under a BSD open-source license with algorithms that are still commonly used by data scientists such as multi-layer perceptrons, support vector machines and K-nearest neighbours. Torch also supported ensembles -- a popular technique that combines the output of multiple algorithms, usually with a weighted average. It's not just open-source software that contributed to the growth of machine learning.

I have been building technology start-ups since 2003. Throughout the years I observed a trend towards the commoditization of machine learning algorithms and the data wrangling tools to deploy these techniques in the real world. The team at Seldon had been hand-crafting recommendation algorithms for a number of years. We adopted Hadoop back in 2011 in order to scale our data processing capabilities beyond programmatic and relational databases. Hadoop had a sister called project Apache Mahout that bundled a variety of machine learning algorithms.

PredictionIO is an open source machine learning server, and is a recent addition to the Apache family. PredictionIO is bundled with HBase, and is used as event data storage to manage the data infrastructure for machine learning models. In this integration task, we will use MapR-DB within the MapR Converged Data Platform to replace HBase. MapR-DB is implemented directly in the MapR File System. The resulting advantages is that MapR-DB has no intermediate layers when performing operations on data.