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Latest Content

    Python or R?

    I am regularly asked by my customers to share my thoughts on the perennial R vs Python question: which one should I learn and use for doing advanced analytics? This article will give you a clear and a simple answer (hint: use both).

    • 11 May 2021
    • 1368 views

    Microsoft Machine Learning Technologies: View Towards 2020

    New Azure Machine Learning: Performance Metrics

    What is new in the new Azure Machine Learning? What is changing in the rest of the Microsoft machine learning platform, notably ML Server and SQL Server ML Services, the 2019 Big Data Clusters, and frameworks: Automated ML, ML.NET, MicrosoftML, RevoScale, and MLLSpark? You will also see an overview of the popularity of non-Microsoft tools in this video—make sure to read the essay, under the video, too.

    • 24 December 2019
    • 1105 views

    Next Year in Machine Learning, Data Science, AI and BI

    ML, BI, DS, and AI Trends that Shaped 2019

    The trends that shaped 2019 and predictions for the future of machine learning and analytics. Why you should abandon Hadoop, brush up on statistics and obsess less about technology.

    • 24 December 2019
    • 2539 views

    Machine Learning for IT Security: From ML to Security AI

    Security Artificial Intelligence

    This video explains how to get started with machine learning for IT security purposes, leading to powerful, potentially dangerous, autonomous Security AI systems.

    • 4 October 2019
    • 320 views

    Machine Learning for Security Applications: Why?

    Hugh Simpson-Wells Interviews Rafal Lukawiecki about Machine Learning for Security Applications

    This interview with Rafal Lukawiecki and Hugh Simpson-Wells discusses applications of machine learning for IT security purposes, including: authentication, authorisation, log analysis, and breach prevention.

    • 31 August 2019
    • 530 views

    The Future of AI—How to Avoid Artificial Stupidity

    The Future of AI—How to Avoid Artificial Stupidity

    In this detailed video I explain how to get started in building not just good AI, but, above all, the kind that avoids the risks of artificial stupidity, by combining several powerful approaches: machine learning, programming in logic, and modern data.

    • 21 March 2019
    • 313 views

    What is Artificial Stupidity?

    What is Artificial Stupidity?

    Artificial Intelligence of today easily becomes Artificial Stupidity. This short video explains its dangers, and suggests when it is OK to use AI.

    • 21 March 2019
    • 1056 views

    What is Artificial Intelligence?

    What is Artificial Intelligence?

    This video introduces the history of Artificial Intelligence (AI) and explains how it can be implemented using Machine Learning.

    • 21 March 2019
    • 977 views

    Additional Code and Data Samples (R, ML Services, SSAS)

    Download code and the data for a few of the demos used in Rafal’s Practical Machine Learning and Practical Data Science courses, including: classifier performance in R, mortgage default logistic regression and the 10 million row data set, cross-sell and recommendations using Association Rules in SQL Server Analysis Services Data Mining.

    • 23 December 2016
    • 1215 views

    How to Succeed with Your First Data Science Projects

    I have had my share of successful and failed projects since I have embarked on data science ten years ago. Let me share some thoughts on setting customer expectations and on choosing the right projects to dive into.

    • 25 October 2016
    • 2316 views

    What is Advanced Analytics, Data Science, Machine Learning—and What is their Value?

    One of the common question Rafal gets asked by budding data scientists is: how can I explain the value of data science to my customers? This article explains the five key reasons for doing advanced analytics in terms of the short-term and strategic value it provides to business customers.

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