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10 of the best data science blogs to follow

There are many very good resources on data science, and it can be a bit overwhelmed to know where to start. This article will include some of the most useful blogs and websites for everyone – from data science experts to complete beginners. In addition to offering advice and learning resources, the list of data science blogs is also full of websites to continue to get information about the news, trends, and opinions today from professionals.

 

If you just start and want to learn a little more about the subject itself, also check our best list of books about data science for beginners (links).

 

  1. Data Science Science

Central Science Data did exactly what it was necessary and acted as an online resource hub for almost all related to data science and large data. This site includes a variety of data science topics about analytics, technology, tools, data visualization, code, and job opportunities. Industrial experts contribute to discussion and insight into the main topics.

 

This site renewed frequently, almost two blog posts a day from authors who contribute and also offer a community forum for discussion or questions.

 

  1. SmartData Collective.

SmartData Collective is a community site that focuses on trends in business intelligence and data management. Similar to data science central, it also displays insight into data science through contributions by industry experts. Where the science of the central data focuses directly on the science of data as a whole, SmartData Collective sees a broader field and how data science can intersect with business.

 

  1. What is big data?

What is big data? Take a different approach with data science and focus on the impact of large data growth into the current digital behemoths. Founder of Blog, Gil Press, intimately familiar with large data and data science, after spending a career in data research and now carrying out the practice of consultation.

 

On his blog, the press explores how much data interacts with our lives and influences everything from technology to business and policy. He provides news sources and comments in the data field.

 

  1. No free hunch

This blog is slightly different from the others, offering direct views to the minds of data scientists, as well as tutorials and news. This is a blog from the Kaggle data science website, which accommodates projects and data science competitions that challenge scientists’ data to produce the best models for superior data sets. Organizations can post their data problems with the number of prizes and professional data will enter to solve it. Crowdsourcing ensures that the experiment is innovative and interesting – and offers many perspectives to learn.

 

More than 200 competitions have been running, including high profiles such as increasing the recognition of the Microsoft Kinect movement, increasing the search for Higgs Boson in CERN, and the famous Heritage Health Award $ 3 million to increase predictions about which patients need to visit hospitals. Kaggle’s official blog deeper into this competition offers interviews with winners to discuss their approach to solving data science problems. This blog also displays news and tutorials for all levels of data science fans.

 

  1. Insidebigdata.

InsideBigData focuses on the learning side of the machine from data science training. It includes large data in it and business, engine learning, in-depth learning, and artificial intelligence. Guest features offer insight into industrial perspectives, while the news and editorial choice articles highlight important events in the field. All articles are categorized neatly by topic to zero on any subject. This blog also maintains a number of resources for events, work, and research reports, and more. This is a source for anyone who wants to stay up to date with machine learning.

 

  1. Pretty statistically

If you can’t get enough statistics, here’s the blog for you. Run by three professors of biostats, they blog about many statistics in large data and how they are used by data scientists in all types of fields – including themselves. For every new statistician who want to jump into a career, they also have interviews with data scientists about their career and roles in the industry.

 

  1. Datafloq.

Datafloq is run by Mark Van Rijmmenam, the author “thinks bigger: develop a successful data strategy that is successful for your business,” and is a good resource for large data in data science. This blog focuses on aspects of large data business and how to make data science work for organizations. It also displays information about trend technology topics such as blockchain and artificial intelligence. Although most act as resources with articles and insights, DataFloq also tries to connect professionals through postwork, vendors, events and training.

 

  1. Data Science 101

For anyone who wants to enter the field of data science, here is – if solid-start. Ryan Swanstrom has worked in data science for Microsoft, Wells Fargo, and Government Defense Contractors. At present, he consulted as Director of Data Sciences for Consultation Association. On this blog, he shared his valuable experience, tips, and advice on how to become a successful data scientist. The blog extends back to 2012 with extensive archives, which are feasible to dive into direct history over the past few years in the discussion of data science.

 

  1. Dataconomy.

Dataconomy is another resource for candidate data scientists. It features news and normal large technology trends and editorials of industrial experts. But what distinguishes it from other data science hubs is its resources to build careers in data science. This site offers a free IT research library and a beginner’s guide to start. For those who already exist in the industry and want to advance, it also has a database of work and candidates.

 

  1. Data Science Report

Talking about deep resources, science report data collects resources from various formats to get data science into your brain. This site collects courses, articles, books, videos, and free TED talks to help each level of data scientists.

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