Tag: machine learning

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. It is often said that data science jobs are for seasoned professionals, and many job ads still show a preference for a profile with a PhD, with years of experience. Yet, many corporate employers have been disillusioned about the value that a PhD brings to the company. Likewise, many professionals, especially among those who just completed a PhD and were offered their first job, find the work sometimes unrewarding. A PhD may command a slightly higher salary initially, and may be required for a position in a research lab ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Shanthababu P. Guys! I hope you all are enjoyed reading my earlier article Part - I 10/20, and I trust that would be useful for you. Let's discuss the rest of the project quickly. 11. Learn to prepare data for your next machine learning project. Problem Statement & Solution When you’re dealing with NLP based problem statement, we must focus on “Text Data” preparation before you can start using it for any NLP algorithm. The foremost step is that text cleaning and processing is an important task in every machine learning ... Read More

Feed: R-bloggers. Author: sang-heon lee. [This article was first published on K & L Fintech Modeling, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. This post gives a brief introduction to a workflow of machine learning model and mostly used R packages before diving into the details. Given a problem to be solved, all machine learning (ML) models use the same input but different output. It is, therefore, useful to understand a common ... Read More

Feed: SingleStore Blog. Author: . SingleStore and MindsDB recently announced a partnership to advance machine learning innovation and provide machine learning features within the SingleStore database. SinglesStore offers a number of features that enhance training performance for machine learning, in addition to supporting real-time inference. This blog post from MindsDB VP of Business Development, Erik Bovee, outlines this exciting integration.In previous posts we have explored machine learning at the data layer, machine learning on data streams, and handling difficult machine learning problems such as large, multivariate time series and SingleStore offers a number of features and capabilities that enhance machine ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Roger Max. Machine learning models make use of training datasets for predictions. And, thus labeled data is an important component for making the machines learning and interpret information. A variety of different data are prepared. They are identified and marked with labels, also often as tags, in the form of images, videos, audio, and text elements. Defining these labels and categorization tags generally includes human-powered effort. Machine learning models which fall under the categories of supervised and unsupervised, pick the datasets and make use of the information as per ML algorithms ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Olha Zhydik. With machine learning now being behind many technologies, from Netflix’s recommendation algorithm to self-driving cars, it’s time for businesses to start taking a closer look. In this article, we will discuss the future of machine learning and its value throughout industries. Machine learning solutions continue to incorporate changes into businesses’ core processes and are becoming more prevalent in our daily lives. The global machine learning market is predicted to grow from $8.43 billion in 2019 to $117.19 billion by 2027. Despite being a trending topic, the term ‘machine learning’ is often used ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. This article focuses on the machine learning aspects of the problem, and the use of pattern recognition techniques leading to interesting, new findings about twin primes. Twin primes are prime numbers p such that p + 2 is also prime. For instance, 3 and 5, or 29 and 31. A famous, unsolved and old mathematical conjecture states that there are infinitely many such primes, but a proof still remains elusive to this day. Twin primes are far rarer than primes: there are infinitely more primes than there are twin ... Read More

Feed: SAS Blogs. Author: Radhikha Myneni. This post, written by Radhikha Myeni and Jagruti Kanjia, will demonstrate how easy it is to build and deploy a machine learning pipeline by using SAS and Python. The Model Studio platform provides a quick and collaborative way to build complex pipelines by dragging and dropping nodes from a web-based interface. These pipelines would typically include feature engineering, model building, autotuning of hyperparameters, model interpretation, and model comparison. The capability to fully integrate open-source software into these pipelines adds flexibility and extensibility. This enables data scientists to expand their SAS toolbox with additional technologies ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Roger Max. Transcending human perception, today autonomous vehicles or AVs have become a reality. Auto giants such as Tesla, BMW, Google, Volkswagen and Volvo have been the front runners in introducing autonomous transportation to ease the pressure off. Meanwhile, the market growth for AV or autonomous vehicles is estimated to touch 40% of CAGR, annually in the next six years. Before going further, it would be worth knowing how vehicles can function autonomously. An AV or autonomous vehicle is equipped with a vision system, LIDAR or radar based sensing and multiple ... Read More

Feed: SAS Blogs. Author: Nick Johnson. This article was co-written by Marinela Profi, Product Marketing Manager for AI, Data Science and Open-Source. Check out her blog profile for more information. Artificial Intelligence (AI) is changing the way people and organizations improve decision-making and move about their lives – from text translation, to chatbots and predictive analytics. However, many organizations are struggling to realize its potential as model deployment processes remain disconnected, creating unforeseen headaches and manual work. Additionally, other requirements like performance monitoring, retraining, and integration into core business processes must be streamlined for optimal teamwork and resource usage. SAS ... Read More