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Some of our advice is generally applicable for working on machine learning and specifically deep and/or reinforcement research projects. However, some of it is only important when faced with the time constraints of a three-month project and are considerably less important when you just started the journey of a three to five year Ph.D. degree. Lofi maker

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Most machine learning classification algorithms are sensitive to unbalance in the predictor classes. Let’s consider an even more extreme example than our breast cancer dataset: assume we had 10 malignant vs 90 benign samples. A machine learning model that has been trained and tested on such a dataset could now predict “benign” for all ...

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I am a final year undergraduate in the Department of Mathematics and Statistics, IIT Kanpur. I am genuinely interested in maths, with statistics being my newfound passion. Recently, I’ve been working on Bayesian statistics, and its power to simplify problems significantly continues to amaze me (given you have the right belief!). Sophia: Many ideas you want to implement in your projects may have already been tackled, you can locate your resources on a variety of coding platforms. Everyone is learning at different experience levels and ages; I took an Intro to Python class in middle school, however I did not start picking up coding again until this year.

The Kinect 2-Chain was a project I worked on for HackMIT 2015. The goal of the project was to aid the visually impaired in navigation. We used a Kinect 2 to map the space in front of the user and send stereo audio signals with varying pitch to indicate the direction and distance of obstacles.

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