Actionable takeaways from a memorable experience As we moved into August and summer begins to wind down, I thought I'd take the time to reflect on my last 12 weeks as a Data Science Intern for Unity Technologies in San Francisco, CA.
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The essential mathematics necessary for Data Science can be acquired with these 15 MOOCs, with a strong emphasis on applied algebra & statistics.
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Machine Learning opportunities can be sparse, so when you finally get invited to that long-awaited Machine Learning Interview, you want it to go perfectly. Let me show you how.
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Harvard Business Review has regarded data scientist as the sexiest job of the 21stcentury. In this article, with the assistance of Octoparse V7, one of the best free web data scraping tool, we aggregated the resources and tools that you may need to become a data scientist.
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I recently had the chance to use machine learning to address an issue that is at the forefront of the American media, the difficulty of recognizing fake news.
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Nowadays, there is a huge list of powerful data visualization tools to help you illustrate your ideas, visualize your data, make it talk, share your significant analytics with customers and the global community.
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What You Need to Know about Machine Learning. This eBook offers you the perfect place to lay the foundation for your work in the world of Machine Learning, providing the basic understanding, knowledge, and skills that you can build on with experience and time.
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I hope Part 1 sold you on the idea that version control is a critical tool for managing data science experiments. But the devil is in the details, so let's talk about how to implement version control in a data science project.
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A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.
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This curated list of mindset-changing books will help you become a better Data Scientist
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I was listening to an old episode of Partially Derivative, a podcast on data science and the news. One of the hosts mentioned that we're now living in the "golden age of data science instruction" and learning materials. I couldn't agree more with this statement. Each month, most publishers seem to have another book on the subject and people are writing exciting blog posts about what they're learning and doing.
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Useful tips to get started writing about your data science projects
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How do you think data science will change over the next 10 years? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
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Deep Learning is one of the hottest technologies out there. There are many research papers in Deep Learning, and it can be really overwhelming to keep up.
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Data Science is quite a large and diverse field. As a result, it is really difficult to be a jack of all trades. Traditionally, Data Science would focus on mathematics, computer science and domain expertise.
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As someone who has been there, I'd like to outline a few practical ideas to help junior data scientists get started at a small software company. The steps were drawn from my personal journey and that of others before me.
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We asked our LinkedIn group members what their greatest challenges were to becoming fully fledged data scientists. Some of the most common frustrations were:
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It has been a while even since I posted on Medium. Having been in Data Science for almost half a year, I've made a lot of mistakes and learned from the mistakes along the wayâ?¦ through the hard way.
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