Github has become the goto source for all things open-source and contains tons of resource for Machine Learning practitioners. We bring to you a list of 10 Github repositories with most stars. We have not included the tutorial projects and have only restricted this list to projects and frameworks
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Github has become the goto source for all things open-source and contains tons of resource for Machine Learning practitioners. We bring to you a list of 10 Github repositories with most stars. We have not included the tutorial projects and have only restricted this list to projects and frameworks
Source: AIM16770
For the past month, we ranked nearly 250 Machine Learning Open Source Projects to pick the Top 10.
Source: medium.mybridge.co13548
We examined 140 frameworks and distributed programing packages and came up with a list of top 20 distributed computing packages useful for Data Science, based on a combination of Github, Stack Overflow, and Google results.
Source: Kdnugget15942
As an organizer for a data science meetup group, I am often asked this question.
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Microsoft acquires GitHub for $7.5B and this is a big deal particularly in Microsoft traditional approach to developers. GitHub is the world's leading software development platform and its customers are Hulu, PayPal, slack, Etsy, Airbnb, GroupOn, Twitch Mailchimp, Coinbase and Braintree and many more.
Source: HOB12117
AI has already changed out lives today. Currently, we already have AI pervading our software systems, particularly those that we, as consumers, use everyday.
Source: HOB4833
This article list data sets from the data science world that you might find interesting.
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We covered 50 data sets for data scientists that are amusing in part 1. In part two we cover 50 more of those.
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50 data sets that data scientist find amusing.
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If you want to become more data driven than you should have good understanding of all the languages and you're supposed to be master in Data Science field as well. Building the first data project is actually not that hard only you should know the basic steps and categorize them from raw data to building a machine learning model.
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Without recognizing our weak points, we'll never be able to overcome them. If modern job interviews of Data Scientist have taught us anything, it's that the correct answer to the question. "What's your biggest weakness" is "I work too hard." If we never admit our deficiencies, then we can't take the steps to address them.
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Thousands of programming languages exist, but there are some trusty ones that developers turn to again and again. GitHub, the startup at the center of open-source software development, tracks these programming trends.
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GitHub has identified three features that make a programming language popular in 2018.
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In the course of recent years, users have doubtless seen quantum jumps within the quality of a good scope of normal innovations. Most clearly, the speech recognition functions on our cell phones work far better to something they want to. After we utilize a voice direction to decision our mates, we have a tendency to contact them currently.
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Now when everyone is moving from papers to the digital world, the race has begun. Now, having basic knowledge about the programming language tech is not sufficient. Learning how to express in the web world has now become a necessity.
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Through wide research, there are multiple technologies which are upcoming continuously that have the most persistent auto labeling for creating the training data which is affordable and consumes time. The area of research which is getting the extreme attention is Snorkel.
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How do I get started with machine learning? This video is a three-month guide which will help you go from an absolute beginner to proficient in the art of machine learning.
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Online code repository GitHub has pulled together the 10 most popular programming languages used for machine learning hosted on its service, and, while Python tops the list, there are a few surprises.
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Because we are humans and have more inclination towards visualization and interaction, learning from videos is the best thing that we can do to ourselves. For this regard I have come up here with the 10 most popular YouTube videos on Data Science to kick start off your career in Data Science.
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This is a new example of style transfer where ML identifies the essential characteristics of a genre in order to create its own examples, such as we've seen before with art and even with cooking.
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Everyone holds equal potential, and the chance to learn programming language easily. Today, we will show you a list of top websites that will help to learn to program.
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Launch Your Career in Data Science. A ten-course introduction to data science developed and taught by leading professors.
Source: HOB3969
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