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    Top 15 Python Libraries for Data Science in 2017

    Core Libraries. 1. NumPy  When starting to deal with the scientific task in Python, one inevitably comes for help to Python’s SciPy Stack, which is a collection of software specifically designed for scientific computing in Python (do not confuse with SciPy library, which is part of this stack, and the community around this stack). This […] More

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    Data Science & Machine Learning Platforms for the Enterprise

    You’ve built that R/Python/Java model. It works well. Now what? “It started with your CEO hearing about machine learning and how data is the new oil. Someone in the data warehouse team just submitted their budget for an 1PB Teradata system, and the the CIO heard that FB is using commodity storage with Hadoop, and […] More

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    Why R is the best data science language to learn today

    In last week’s blog, I explained why you should Master R (even if it may eventually become obsolete). I wrote that article to address people who claim mastering R is a bit of a waste of time (because it will eventually become obsolete). But when I suggested that R may eventually become obsolete, this seemed […] More

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    The Difference Between Data Science and Data Analytics

    However, although they may sound similar, the terms are often quite different and have differing implications for business. Knowing how to use the terms correctly can have a large impact on how a business is run, especially as the amount of available data grows and becomes a greater part of our everyday lives. Data Science […] More

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    Deep Learning 101: Demystifying Tensors

    Ted Dunning, Chief Applications Architect at MapR Technologies. Tensors and new machine learning tools such as TensorFlow are hot topics these days, especially among people looking for ways to dive into deep learning.  Turns out, when you look past all the buzz, there’s really some fundamentally powerful, useful and usable methods that take advantage of […] More

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    What does it take to be data scientist at Uber

    BigInsights Principal Raj Dalal met up with Uber’s Chief Data Architect M C Srivas on a recent visit to San Francisco, where, in the course of the hour-long conversation, Srivas spoke of what data analytics meant for Uber, and how data innovation was being used to further, what is now popularly known around the world […] More

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    The Science of Quality Growth

    Growth is not about moving metrics using anecdotes and short-term tactics. A healthy and sustainable growth plan should go hand-in-hand with great products that ensure members continue to receive increasing value. When strategized correctly, growth can generate long-term sustainable boosts to engagement and retention, which ultimately leads to revenue and profits. When strategized incorrectly, growth […] More

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    Getting Started with Cloudera Data Science Workbench

    Last week, Cloudera announced the General Availability release of Cloudera Data Science Workbench. In this post, I’ll give a brief overview of its capabilities and architecture, along with a quick-start guide to connecting Cloudera Data Science Workbench to your existing CDH cluster in three simple steps. At its core, Cloudera Data Science Workbench enables self-service data […] More

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    12 Best Practices for Big Data and Data Science

    Get your data in order. The right data management strategy is important to big data and data science success. In the zeal to get started analyzing data, organizations often don’t pay attention to that data. Yes, it is OK to experiment on raw data; a good data scientist usually explores the data before building models—particularly […] More

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    The State of Big Data and Data Science

    Although there has been a lot of market hype and excitement around big data and data science, this does not necessarily mean that it has widely penetrated in most organizations. As previously mentioned, a little more than a third of our respondents believe they have a big data and analytics program in place now, and […] More

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    Demystifying Data Science

    [Opening Scene]: Billy Dean is pacing the office. He’s struggling to keep his delivery trucks at full capacity and on the road. Random breakdowns, unexpected employee absences, and unscheduled truck maintenance are impacting bookings, revenues and ultimately customer satisfaction. He keeps hearing from his business customers how they are leveraging data science to improve their business […] More

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    The hard to find Data Scientist

    One of the biggest things that can put a damper on big data analytics programs has nothing to do with deploying and managing advanced analytics tools—it’s the challenge of hiring and retaining skilled data scientists who can put the tools you’ve installed to good use. In a survey of business intelligence, analytics and data management […] More

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    Building the LinkedIn Data Science Team

    Reference: Building Data Science Teams ,The Skills, Tools, and Perspectives Behind Great Data Science Groups – DJ Patil I’m proud of what we’ve accomplished in building the LinkedIn data team. However, when we started, it didn’t look anything like the organization that is there today. We started with 1.5 engineers (who would later go on to invent […] More

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    The Roles of a Data Scientist

    In every organization I’ve worked with or advised, I’ve always found that data scientists have an influence out of proportion to their numbers. The many roles that data scientists can play fall into the following domains. Decision sciences and business intelligence Data has long played a role in advising and assisting operational and strategic thinking. […] More

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    Finding Radiohead’s most depressing song, with R

    Data scientist and R enthusiast Charlie Thompson ranked all of their tracks according to a “gloom index”, and created the following chart of gloominess for each of the band’s nine studio albums. (Click for the interactive version, crated with with highcharter package for R, which allows you to explore individual tracks.) If you’re familiar with the […] More

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    Insights-Driven practices using Data Science Tools

    In September 2016, DataScience commissioned Forrester Consulting to examine the differences between high-growth firms using insights-driven practices such as data science, and everybody else. Specifically, they wanted to find out if a platform that unifies the entire life cycle of data science work could accelerate a firm’s competitive advantage through insights. Forrester conducted 10 in-depth […] More

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    Easy-to-use data science tools power new startup

    More data science tools are available today than ever before, and that’s good news for companies occupying smaller niches. It means they have access to tools that fit their needs, whether large or small. “We’re dealing with a very unique niche of organizations, so it’s different than if you’re at Amazon,” said Brian Johnson, co-founder […] More

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    Who does what in the Data Science Industry (Infographic)

    Team Bisilo We are a team of Data Enthusiast scouring the web for the latest on #DataScience, #MachineLearning, #BigData, #Security, #PredictiveAnalytics, from the TOP leading authorities on the matter. All in one place you can read the trending news on the topics. https://www.bisilo.com More

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    Data Science: Data Culture and Career Tips at WiDS2017

    What a movement! The event featured data science leaders from academia, industry, non-profits, and government talking about research, technology, and careers in the field. Attendees ranged in experience from current students to B.Sc.s and Ph.D.s. In all, 114 companies and 31 universities were represented. The energy and intelligence on display were truly inspiring. At LinkedIn, one […] More

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    Women in Data Science, Strength and Empowerment

    On Friday February 3rd, took place the Women in Data Science Conference (#WiDS2017), which happened at 80+ locations worldwide with live stream from Stanford University. It was an amazing event, where you were able to learn how many professional women are making sense out of data, their latest data science related researches in multiple domains […] More

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    Data Scientist Interview Series: Q&A with Davi Abdallah

    Davi Abdallah is the Data Scientist at JetSmarter, the fastest growing private jet company in the world. Davi started his career as a Systems Analyst, and worked his way up into the BI/Data field. He worked for top companies like Wells Fargo, Microsoft and AutoNation. Here are Davi’s words on his world as a Data Scientist. Kassandra: […] More

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    Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

    As data science is a broad discipline, I start by describing the different types of data scientists that one may encounter in any business setting: you might even discover that you are a data scientist yourself, without knowing it. As in any scientific discipline, data scientists may borrow techniques from related disciplines, though we have […] More

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    Should I Run with a Pace Group

    Probably, at least according to data from the Dublin City Marathon. TLDR; Should I run with a pace group? Based on the data from the Dublin City Marathon, if there is a pace group that matches your target time then it is likely to help your performance on the day. Pace groups do have an […] More

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    Building The LinkedIn Knowledge Graph

    An important component of this technology stack is a knowledge graph that provides input signals to machine learning models and data insight pipelines to power LinkedIn products. This post gives an overview of how we build this knowledge graph. LinkedIn’s knowledge graph LinkedIn’s knowledge graph is a large knowledge base built upon “entities” on LinkedIn, […] More