Data Science News – handpicked articles, news, and stories from Data Science world.

Data Science News – handpicked articles, news, and stories from Data Science world. NEWS   Experts Predict When Artificial Intelligence Will Exceed Human Performance – Artificial intelligence is changing the world and doing it at breakneck speed. The promise is that intelligent machines will be able to do every task better and more cheaply than humans. Rightly or wrongly, one industry after another is falling under its spell, even though few have benefited significantly so far.   This app uses artificial intelligence to turn design mockups into source code – While traditionally it has been the task of front-end developers […]

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Validate-test a predictive model.

  Validate-test a predictive model. Why evaluate/test model at all? Evaluating the performance of a model is one of the most important stages in predictive modeling, it indicates how successful model has been for the dataset. It enables to tune parameters and in the end test the tuned model against a fresh cut of data. Below we will look at few most common validation metrics used for predictive modeling. The choice of metrics influences how you weight the importance of different characteristics in the results and your ultimate choice of which machine learning algorithm to choose. Before we move on to […]

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Machine Learning with TensorFlow Intro

Machine Learning with TensorFlow Intro. What is TensorFlow? The shortest definition would be, TensorFlow is a general-purpose library for graph-based computation. But there is a variety of other ways to define TensorFlow, for example, Rodolfo Bonnin in his book – Building Machine Learning Projects with TensorFlow brings up definition like this: “TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) passed between them.” To quote the TensorFlow website, TensorFlow is an “open source software library for numerical computation using data […]

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Learn TensorFlow for free.

Below a list of free resources to learn TensorFlow: TensorFlow website: www.tensorflow.org Udacity free course: www.udacity.com Google Cloud Platform: cloud.google.com Coursera free course: www.coursera.org Machine Learning with TensorFlow by Nishant Shukla : www.tensorflowbook.com ‘First Contact With TensorFlow’ by Prof. JORDI TORRES: jorditorres.org  or you can order from Amazon: First Contact With Tensorflow Kadenze Academy: www.kadenze.com OpenShift: blog.openshift.com Tutorial by pkmital : github.com Tutorial by HyunsuLee : github.com Tutorial by orcaman : github.com Stanford CS224d: Lecture 7 Was the above useful? Please share with others on social media. If you want to look for more information, check some free online courses available at   coursera.org, edx.org or udemy.com. Recommended reading […]

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Numerai deep learning example.

In a previous post on Numerai, I have described very basic code to get into a world of machine learning competitions. This one will be a continuation, so if you haven’t read it I recommend to do it- here. In this post, we will add little more complexity to the whole process. We will split out 20% of training data as validation set so we can train different models and compare performance. And we will dive into deep neural nets as predicting model. Ok, let’s do some machine learning… Let’s start with importing what will be required, this step is […]

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Machine learning competitions – Numerai example code.

In this post, I want to share, how simple it is to start competing in machine learning tournaments like Numerai. I will go step by step, line by line explaining what is doing what and why it is required. Numerai is a global artificial intelligence competition in predicting financial markets. Numerai is a little bit similar to Kaggle but with clean datasets, so we can pass over long data cleansing process.  You just download the data, build a model, and upload your predictions, that’s it. To extract most of the data you would initially do some feature engineering, but for […]

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