Data Scientist in the making

A curated list of articles from my continous learning journey

15 Useful Python Libraries to make your Data Science tasks Easier

Python has become a big hit in the Data Science community over the last five years. So much so that it is slowly taking over R – the ‘lingua franca of statistics’ – as the preferred choice of tool for many, as this recent poll conducted by KDNuggets suggests….

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How VW Predicts Churn with GPU-Accelerated Machine Learning and Visual Analytics

MapD is a founding and active member of GOAi (the GPU Open Analytics Initiative). One of the primary goals of GOAiI is to enable end-to-end analytics on GPUs….

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Google Wanted to Know What Makes a Manager Great, So It Conducted a Study. Here Are the Results

20 years ago, you probably would’ve laughed if someone said your life would one day be irrevocably changed by a company called Google. What’s a google? But, as you know, Google’s become the largest entity in one of the biggest tech companies in the world….

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4 Years of Data Science at Schibsted Media Group

In 2014, I joined a small team at Schibsted Media Group as the 6th Data Scientist in the organisation. Since then, I’ve worked on many data science initiatives in an organisation that now houses 40+ Data Scientists….

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How to build your own AlphaZero AI using Python and Keras

In March 2016, Deepmind’s AlphaGo beat 18 times world champion Go player Lee Sedol 4–1 in a series watched by over 200 million people….

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On-Demand Webinar – AI Development Using Data Science VMs (DSVM), Deep Learning VMs (DLVM) & Azure Batch AI

This post is authored by Barnam Bora, Program Manager in the Cloud AI group at Microsoft. Microsoft’s Data Science Virtual Machines (DSVM) and Deep Learning Virtual Machines (DLVM) are a family of popular VM images in Windows Server and Linux flavors that are published on the Azure Marketplace….

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Neural Networks for Beginners: Popular Types and Applications

Today, neural networks are used for solving many business problems such as sales forecasting, customer research, data validation, and risk management. For example, at Statsbot we apply neural networks for time series predictions, anomaly detection in data, and natural language understanding….

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Six Step Data Analysis Methodology

For every data analysis project I work on, I utilize a structured methodology to ensure that there is a systematic process to get to insight rather than stumbling my way to it. In addition, for my day-to-day work I’ve adapted the Cookie Cutter Data Science Repo to fit with this methodology….

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Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

Customer churn is a problem that all companies need to monitor, especially those that depend on subscription-based revenue streams….

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