Overview about Akassh

With years of experience, ranging from front end development, to data and pipeline engineering, with some low level robotics and compiler optimizations, and some ML model implementation, I feel confident to say I am a well rounded engineer, able to handle a vast spread of projects.

With the right captain and crew, a ship can cross the greatest of oceans and overcome the greatest of maelstorms. To see myself overcome storms and whirlpools in different settings and projects, I know what it takes to successfully manouver a ship of many scales.

Some of my many
talents and expertise

One of my most recent projects has been to hook up a phone app that I wrote to make low level communication to a socket on a Raspberry Pi 2 to control a car. This alone taught me a lot, for example the benefits of git and repositories.

Throughout my college, I have also been deeply invested in writing programs in python and a lot of my research with neural networks came about because of it. I have also been trying to write my own pip packages and packages for the OpenAI Gym projects. This gave me a further understanding of what it takes to delve into different aspects that go into making an open-source project.

Along my learning, I really found myself relying on cloud computing a lot to do some server tasks rather than having to port forward my own personal computer from home. This makes me appreciate the backend field a lot more with their server-management skills and deployment.

Some of my Projects

Other than spending time with friends and family, I am very passionate about working on something new,
even if it has been done by someone else in the world previously. It helps me grow.

Car Controller

I decided to make an Android app to control my RC car after I messed up with the electronics so that it receive WiFi Signals, and not Radio Signals. After that, I had to create a protocol for both ends to adhere to.

Receiver

This little repository of code is the compliment of the Car Controller. It has the code and instructions to set up the raspberry pi (or a microcontroller like an Arduino) to run so that it can act as a receiver for signals over WiFi and send out electrical signals through to GPIO pins to control the motors, servos and lights.

Mouse Maze

When I was first starting out with neural networks and reinforcement learning, the OpenAI Gym environments were very handy for testing. For theoretical stuff, I was constantly looking back at a Mouse in a Maze. Unfortunately, there was no such environment for me to actually practice with code. Hence I started this project, very detailed like its sibling pip gym environment packets.

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