What are the benefits to online dating? Can't we just meet people in school, at work, or in public? Naturally, we don't all have the finesse to do that. Perhaps we are shy, not into office drama, or just not social enough. 

The benefit to online dating is that we can present ourselves in a wall of text without ever leaving our busy lives. How convenient! Also, we can filter out other users that don't meet our standards rather than asking uncomfortable questions in person. However, with online dating, there are downfalls to the benefits. What if people aren't honest and how do people get quality matches?

This analysis will try to answer and give suggestions to improve the online dating experience. The full paper and code can be found on my GitHub. (I highly recommend you take a look at this if you are interested in the science behind the data!)

There's nothing more important than safety when you are driving a vehicle. Have you ever commuted to work, school, or a frequent place only to arrive with no recollection of what happened during your drive? Do you feel safe? I trust myself, so yes. But not always. The ability that we have to do such things comes from our brain being able to use past events to guide us to drive while continuing to learn as are aware of our surroundings. What we get used to are things like weather, traffic signs, motion, and other objects that we react to. (Hopefully) Our brain uses it to predict what we are likely to do, which could be simply driving to work while avoiding obstacles. However, what if one day, we weren't able to be entirely safe due to fatigue or another factor that our brain cannot simply react fast enough to?

There's nothing more frustrating that waiting in front of an ATM during your lunch break to deposit a check. Many bank patrons today use a feature on their phones to deposit checks which uses their phone cameras. But just how accurate is it to be able to trust? Sadly, we don't have that information available but I would consider anything under 1% error to be excellent. Luckily to us, we can make a neural network to mimic what these apps use. In this project, I will develop a deep learning model to achieve a near state-of-the-art performance on the MNIST handwritten dataset. I'm going to use Keras with TensorFlow.

We can use a neural network to use 5 years of stock data from Yahoo Finance to predict our current year's stock prices. This study is based on a paper from Stanford University.

A house value is simply more than location and square footage. Like the features that make up a person, an educated party would want to know all aspects that give a house its value. A house buyer or even a seller may focus on a few key points on house value such as location or square footage. However, different features give different effects on their presence of each other. For example, a house buyer may want a large house with a backyard in a nice location. However, if the house were to be also in a different state, that may compromise the value of certain features such as square footage. Machine learning can take of this problem a lot easier than regular or even seasoned real estate enthusiasts.

This study uses reproduction data from Yammer, a social network website where coworkers communicate. They can share documents, updates, and ideas by posting then in groups. My goal is to improve their product and business decisions using their reproduction data. With these problems, I will not only focus on SQL syntax, but also about the meaning of the data I measure.

Out of curiosity, I've always wondered what the highest paying data jobs and companies in America are. Since I'm local to Silicon Valley, I've automatically assumed that here is the place to work if I want to earn the most. However, that is not necessarily the case. Salary data from Glassdoor, LinkedIn, and Indeed are inconsistent with each other. Also, cost of living should be factored in to salary data. So how do we present a logical story on the highest paying tech jobs in America? I'm going to use Tableau to make dashboards in order to visualize a story in a clean, compelling format.