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Aggregated news around AI and co.

    Author: chm

    Statistics for Machine Learning (7-Day Mini-Course)

    2. August 2018 chm Uncategorized

    Statistics for Machine Learning Crash Course. Get on top of the statistics used in machine learning in 7 Days. Statistics is a field of mathematics

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    IBM and H2O.ai combine forces to provide machine learning on IBM Power Systems

    2. August 2018 chm Uncategorized

    I wrote this blog on Jun 7, 2018 on IBM’s blog … Collaboration taps POWER9 for open source AI workbench I am delighted to announce our

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    Scaling TensorFlow and Caffe to 256 GPUs

    2. August 2018 chm Uncategorized

    I wrote this story on Aug 7, 2017 on the IBM Blog … Deep learning has taken the world by storm in the last four years,

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    Rules of thumb for Deep Learning

    2. August 2018 chm Uncategorized

    With my few years of experience in training and using various available open source model networks, I have learned the hard way of setting various

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    #APaperADay S1E6: Interpretability Beyond Feature Attribution: Quantitative Testing with Concept…

    2. August 2018 chm Uncategorized

    [link to paper on arXiv] ## Breaking down the title Ask anyone, and they’ll say that machine learning has an interpretability problem. We know what goes

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    End-to-end machine learning workflows using TensorFlow and Labelbox

    2. August 2018 chm Uncategorized

    This post originally appeared on Heartbeat. Motivation The handoff of labeled data from domain experts to machine learning teams is a critical step in machine

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    Deep Learning with a little help from my friends

    2. August 2018 chm Uncategorized

    When you are start in a new field, the best it’s to start with good company, friends or a good community that can answer your

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    Future considerations of Online Marketplaces - Understanding Tendencies and Technologies. Part 2.

    2. August 2018 chm Uncategorized

    In our previous article, we have discussed such technologies as blockchain and virtual/augmented/mixed reality in the context of development of online marketplaces. Let’s look at

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    What Borges Can Tech Us About Overfitting and Underfitting in Deep learning Models

    2. August 2018 chm Uncategorized

    This is an aggregation of various posts I published last year about overfitting and underfitting Overfitting and underfitting are two of the biggest challenges in

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    What is the ‘Deep State?’

    2. August 2018 chm Uncategorized

    Yin and yang (is) zero and-or one. Explaining politics. And (human) Nature. The ‘deep’ ‘state’ in politics, is directly (and, also, indirectly) related to the

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    ICML 2018: An AI party in our own backyard

    2. August 2018 chm Uncategorized

    The Peltarion team just finished an exhilarating week at the 35th International Conference on Machine Learning (ICML). For those of you that attended, we hope

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    Ai Ensembling ways

    2. August 2018 chm Uncategorized

    Many kaggle competitors use Xgboost model to train their data on and it has outperformed every other model. So,on what actually it’s based on ? Its

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