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 Dealing with categorical features in machine learning
Many machine learning algorithms require that their input is numerical and therefore categorical features must be transformed into numerical features before we can use any of these algorithms.
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Annotated Heatmaps of a Correlation Matrix in 5 Simple Steps
A heatmap is a graphical representation of data in which data values are represented as colors. That is, it uses color in order to communicate a value to the reader. This is a great tool to assist the audience towards the areas that matter the most when you have a large volume of data.
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Ten random useful things in R that you might not know about
Because the R ecosystem is so rich and constantly growing, people can often miss out on knowing about something that can really help them in a task that they have to complete
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Scalable Python Code with Pandas UDFs: A Data Science Application
There is still a gap between the corpus of libraries that developers want to apply in a scalable runtime and the set of libraries that support distributed execution. This post discusses how to bridge this gap using the the functionality provided by Pandas UDFs in Spark 2.3+
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How to Automate Hyperparameter Optimization
A step-by-step guide into performing a hyperparameter optimization task on a deep learning model by employing Bayesian Optimization that uses the Gaussian Process. We used the gp_minimize package provided by the Scikit-Optimize (skopt) library to perform this task.
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If you’re a developer transitioning into data science, here are your best resources
This article will provide a background on the data scientist role and why your background might be a good fit for data science, plus tangible stepwise actions that you, as a developer, can take to ramp up on data science.
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Mongo DB Basics
Mongo DB is a document oriented NO SQL database unlike HBASE which has a wide column store. The advantage of Document oriented over relation type is the columns can be changed as an when required for each case as opposed to the same column name for all the rows.
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Animations with Matplotlib
Animations make even more sense when depicting time series data like stock prices over the years, climate change over the past decade, seasonalities and trends since we can then see how a particular parameter behaves with time.
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Becoming a Level 3.0 Data Scientist
Want to be a Junior, Senior, or Principal Data Scientists? Find out what you need to do to navigate the Data Science Career Game.
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Probability Mass and Density Functions
This content is part of a series about the chapter 3 on probability from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016). It aims to provide intuitions/drawings/python code on mathematical theories and is constructed as my understanding of these concepts.
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Dealing with categorical features in machine learning
If you’re a developer transitioning into data science, here are your best resources