Learn Python for Data Science from Scratch

Python is a multipurpose programming language and widely used for Data Science, which is termed as the sexiest job of this century. Data Scientist mine thru the large dataset to gain insight and make meaningful data driven decisions. Python is used as general purposed programming language and used for Web Development, Networking, Scientific computing etc. We will be discussing further about the series of awesome libraries in python such as numpy, scipy & pandas for data manipulation & wrangling and […]

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Why R is Bad for You

Summary:  Someone had to say it.  In my opinion R is not the best way to learn data science and not the best way to practice it either.  More and more large employers agree.   Someone had to say it.  I know this will be controversial and I welcome your comments but in my opinion R is not the best way to learn data science and not the best way to practice it either.   Why Should We Care What […]

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Will Python Replace Java?

  According to the IT programming trend, Java is currently more popular than other programming languages in terms of number of jobs, number of existing Java developers and overall usage statics in IT compared to Python. According to the latest usage statistics posted on a popular Technology Survey site, Java is being used by 3.0% websites as a server-side programming language, whereas only 0.2% of websites use Python. However, all the recent reports have highlighted that the usage and popularity of Python […]

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How to automatically create Base Line Estimators using scikit learn.

For any machine learning problem, say a classifier in this case, it’s always handy to create quickly a base line classifier against which we can compare our new models. You don’t want to spend a lot of time creating these base line classifiers; you would rather spend that time in building and validating new features for your final model. In this post we will see how we can rapidly create base line classifier using scikit learn package for any dataset. […]

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Deep Learning with TensorFlow in Python

Classifying the letters with notMNIST dataset Let’s first learn about simple data curation practices, and familiarize ourselves with some of the data that are going to be used for deep learning using tensorflow. The notMNIST dataset to be used with python experiments. This dataset is designed to look like the classic MNIST dataset, while looking a little more like real data: it’s a harder task, and the data is a lot less ‘clean’ than MNIST. Preprocessing First the dataset needs to be downloaded and […]

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Four great machine learning eBooks

Want to learn machine learning? Looking for data science tutorials and guides to help you master your data and produce actionable, game-changing insights? Look no further than this list of machine learning eBooks from the Packt team…. 1. Python Machine Learning Python Machine Learning is today one of the most popular machine learning titles on the market. And it’s not hard to see why – by bridging the gap between theory and practice, the author Sebastian Raschka provides you with an […]

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Some Analysis with Astronomy data (in Python)

The following figure shows the median FITS file computed from the above FITS files using the binapprox algorithm. 2. Cross-matching When investigating astronomical objects, like active galactic nuclei (AGN), astronomers compare data about those objects from different telescopes at different wavelengths. This requires positional cross-matching to find the closest counterpart within a given radius on the sky. In this activity you’ll cross-match two catalogues: one from a radio survey, the AT20G Bright Source Sample (BSS) catalogue and one from an optical survey, the SuperCOSMOS all-sky galaxy catalogue. The BSS catalogue […]

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Best practices of orchestrating Python and R code in ML projects

Today, data scientists are generally divided among two languages — some prefer R, some prefer Python. I will not try to explain in this article which one is better. Instead of that I will try to find an answer to a question: “What is the best way to integrate both languages in one data science project? What are the best practices?”. Beside git and shell scripting additional tools are developed to facilitate the development of predictive model in a multi-language environments. For […]

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CNN for Short-Term Stocks Prediction using Tensorflow

In machine learning, a convolutional neural network (CNN, or ConvNet) is a class of neural networks that has successfully been applied to image recognition and analysis. In this project I’ve approached this class of models trying to apply it to stock market prediction, combining stock prices with sentiment analysis. The implementation of the network has been made using TensorFlow, starting from the online tutorial. In this article, I will describe the following steps: dataset creation, CNN training and evaluation of […]

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Recommender Engine – Under The Hood

Many of us are bombarded with various recommendations in our day to day life, be it on e-commerce sites or social media sites. Some of the recommendations look relevant but some create range of emotions in people, varying from confusion to anger. There are basically two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them. Content based: In content based recommender systems, keywords […]

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