Microsoft DP-100 – Designing and Implementing a Data Science Solution on Azure – free questions.

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Microsoft Certified Azure Data Scientist Associate, the DP-100 exam measures your ability to accomplish technical tasks like: manage Azure resources for machine learning run experiments and train models deploy and operationalize machine learning solutions implement responsible machine learning Example Questions You need to resolve the local machine learning pipeline performance issue. What should you do? […]

Trading with Python Intro – Data Import

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Traditionally, there have been two general ways of analyzing market data: fundamental analysis – focused on underlying fundamental data technical analysis – focused on charts and price movements In recent years, computer science and mathematics revolutionized trading, it has become dominated by computers helping to analyze vast amounts of available data.  Algorithms are responsible for […]

Data Scientist Interview Questions – Explain what precision and recall are?

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Data Scientist Interview Questions – Explain what precision and recall are.   After the predictive model has been finished, the most important question is: How good is it? Does it predict well? Evaluating the model is one of the most important tasks in the data science project,  it indicates how good predictions are. Very often for […]

How would you validate-test a predictive model?

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How would you 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 […]

Why would you use Regularization and what it is?

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Why would you use Regularization and what it is? In Machine Learning, very often the task is to fit a model to a set of training data and use the fitted model to make predictions or classify new (out of sample) data points. Sometimes model fits the training data very well but does not well […]

Introduction to TensorFlow

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Introduction to TensorFlow. 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 […]

Where to learn TensorFlow for Free?

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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 […]

Tensor Flow Cheat Sheet.

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TensorFlow Quick Reference Table – Cheat Sheet. TensorFlow is very popular deep learning library, with its complexity can be overwhelming especially for new users. Here is a short summary of often used functions, if you want to download it in pdf it is available here: TensorFlow CheetSheet – SecretDataScientist.com If you find it useful please […]

Popular Pandas snippets used in data analysis.

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Popular Pandas snippets used in data analysis. Pandas is very popular Python library for data analysis, manipulation, and visualization, I would like to share my personal view on the list of most often used functions/snippets for data analysis. 1.Import Pandas to Python import pandas as pd 2. Import data from CSV/Excel file df=pd.read_csv(‘C:/Folder/mlhype.csv’)   #imports […]

Numerai – deep learning example code.

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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 […]