Top 5 Python Books for Data Science and Machine Learning Programmers

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While there are many online courses to learn Python for Machine learning and Data science, books are still the best way to for in-depth learning and significantly improving your knowledge. Python is a universal language that is used by both data engineers and data scientists and probably the most popular programming language as well. All the Data Scientists I have spoken and many in my friend circle just loves Python, mainly because it can automate all the tedious operational work that data engineers need to do. To make the deal even sweeter, Python also has the algorithms, analytics, and data visualization libraries like Metaplotlib, which is essential data scientists. In both roles, the need to manage, automate, and analyze data is made easier by only a few lines of code.


Should data scientists using R and Python switch over to Julia?

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It might be time for data scientists to learn a new programming language. Particularly if they have a need for speed. Last week, the lead developers behind the open source programming language Julia announced the 1.0 release of their project. This signals that the language, which is optimized for data analysis and machine learning, is no longer a work in progress. Julia code written in the 1.0 version will still work even when new versions are released--by contrast, code written in version 0.4 was not guaranteed to work under version 0.6.


Which Programming Language Is Best for Big Data? 7wData

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Nothing is quite so personal for programmers as what language they use. Why a data scientist, engineer, or application developer picks one over the other has as much to do with personal preference and their employers' IT culture as it does the qualities and characteristics of the language itself. But when it comes to Big Data, there are some definite patterns that emerge.


KDnuggets News 16:n23, Jun 29: Machine Learning Trends & Future of AI; Data Science Kaggle Walkthrough; Regularization in Logistic Regression

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Doing Data Science: A Kaggle Walkthrough Part 6 - Creating a Model Top Machine Learning Libraries for Javascript Improving Nudity Detection and NSFW Image Recognition History of Data Mining Predictive Analytics World in October: Government, Business, Financial, Healthcare Software 5 More Machine Learning Projects You Can No Longer Overlook BigDebug: Debugging Primitives for Interactive Big Data Processing in Spark Achieving End-to-end Security for Apache Spark with Databricks Predicting purchases at retail stores using HPE Vertica and Dataiku DSS Tutorials, Overviews, How-Tos Mining Twitter Data with Python Part 4: Rugby and Term Co-occurrences Ten Simple Rules for Effective Statistical Practice: An Overview Mining Twitter Data with Python Part 3: Term Frequencies Opinions The Big Data Ecosystem is Too Damn Big An Inside Update on Natural Language Processing From Research to Riches: Data Wrangling Lessons from Physical and Life Science News Top Stories, June 20-26: New Machine Learning Book, Free Draft Chapters; Machine Learning Trends & Future of A.I. Webcasts and Webinars Webinar, Jun 30: Introducing Anaconda Mosaic: Visualize. Bank of Ireland: Senior Data Scientist within the Advanced Analytics Team DuPont Pioneer: Data Scientist - Encirca Academic U. of Iowa: Business Analytics & Information Systems, Lecturer U. of Iowa: Lecturer: Business Analytics & Information Systems Top Tweets Top KDnuggets tweets, Jun 15-21: Predicting UEFA Euro2016; Visual Explanation of Backprop for Neural Nets Quote "Everything at scale in this world is going to be managed by algorithms and data ... every business will be an algorithmic business."