Where to spend your precious time to stay in-demand

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Eventually, the Data Scientist title as we know it now will go away, and having specialized knowledge or skills will qualify you for jobs and differentiate you from the crowd. Depending on your interests or where you want to work, spending your precious time on one (or maybe two) of the following areas shows you have intention in your studies and will fit into your schedule. The focus areas I describe are what I think are the four broad areas that Data Science will split into. …

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Manipulating pandas data frames is a common task during exploratory analysis or preprocessing in a Data Science project. Filtering and sub-setting the data is also common. Over time, I have found myself needing to select columns based on different criteria. I hope readers find this article as a reference.

Example Data

If you want to use the data I used to test out these methods of selecting columns from a pandas data frame, use the code snippet below to get the wine dataset into your IDE or a notebook.

from sklearn.datasets …

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My personal feeling is that large companies could benefit from having scientifically minded and data driven people in positions of leadership, especially in areas responsible for innovation and making data driven decisions. For anyone working as a Data Scientists at a big company: think about where you want to go next in your career and start making moves early in your career to show your interest and gain critical experience.

Types of Growth for Data Scientists

Data Scientist is already, by itself, a high level technical role which usually requires a higher education and/or more experience. Still, there is always room to grow, but you need…

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Working as a Data Scientist is definitely a privilege, and a role that I have enjoyed for years. While most interactions are professional and enjoyable, there are a few personas that I have experience working with as a data scientist that I think others can relate to. I’ll share what I feel are the 4 most difficult to work with, and give some tips on what you can do to make your workplace more conducive to data science.

The Task Master

When deciding on which color to paint the walls in your kitchen, has anyone ever suggested to paint the kitchen every color…

Train a neural network to predict two different targets simultaneously.

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Using a network of nodes, you can train models that take into account multiple targets and even targets of different types. I thought this was so great the first time I tried it on an actual project and it opened up my perception of what neural networks can do. In this article I’ll talk about how you can train a neural network to predict two different targets simultaneously. …

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When someone shows you who they are, believe them the first time. — Maya Angelou

You reach out your hand, grasp the door handle, turn it and push open the door. As it gently swings open and comes to a rest, you see 3 people: two are laughing and talking with each other and one is staring at their phone with an angry look. Does this quick information tell you anything about how to communicate with the people in this room? Obviously, after you learn more about them you will have a better idea on how to approach them. This…

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Here, I will share with you two different methods for applying custom functions to groups of data in pandas. There are many out-of-the-box aggregate and filtering functions available for us to use already, but those don’t always do everything we want. Sometimes, when I want to know “what was the second most recent observation per month” or “what is the difference between two weighted averages by product type”, I know I need to define a custom function to do the job.

Sample Data (not again…)

Usually, I try not to use this toy dataset because it has been done so many times, but it…

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An airport in Florida is closer to the Detroit airport than one in Hyderabad, and we know that because we measure the distances using latitude and longitude (Hyderabad is a huge city in India). But, how do we say one shopping basket’s contents are closer to another’s? Or one forest is more similar to another in terms of the animals that live in them? We can treat these as comparisons between sets and measure the similarity (or dissimilarity) between them using Jaccard’s coefficient (We’ll use coefficient and similarity score interchangeably). For large datasets, this can be a big task, so…

Binary Classification from Scratch in Python

There is no shortage of articles, videos and tutorials on logistic regression for classification. It’s a classic subject in Machine Learning and is usually a stepping stone before moving on to more complex algorithms. What this article aims to do is show you logistic regression from another lens, where we can solve for a formulaic solution to the weights that we pass to a model that returns the predicted probability. I provide links to the code and solution in the article.

The problem that Logistic Regression aims to tackle is that of finding the probability of an observation of a…

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Testing candidates for a Data Scientist position gives a hiring organization a great sense of how well they can do job-related tasks and manage time effectively. Skills that Data Scientists need to succeed vary by company or even by teams within a company, so testing candidates should be tailored. In general though, Data Science is a process that includes many steps and independent skills that aggregate to something greater than the sum of its parts. …

Casey Whorton

Data Scientist | British Bake-Off Connoisseur| Recovering Insomniac | Heavy Metal Music Advocate

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