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Hi there πŸ‘‹

I'm Daniel D. Tripp, a passionate and results-driven Software Engineer from San Francisco. Welcome to my GitHub profile! πŸ‘¨β€πŸ’»

Here's a glimpse into what I'm up to:

  • πŸ”­ Recently Worked On: Enhancing data security and automation and contributing to Kubernetes infrastructure.

  • 🌱 Currently Learning: Always expanding my knowledge in distributed systems, cloud computing, and exploring new tools and technologies.

  • πŸ‘― Looking to Collaborate On: Open to collaboration on projects related to cloud infrastructure, Kubernetes, and full-stack development.

  • πŸ€” Looking for Help With: Always open to learning from others, especially in areas like machine learning and advanced data analytics.

  • πŸ’¬ Ask Me About: My experiences in software engineering, cloud technologies, or any questions related to my projects and experiences.

  • πŸ“« How to Reach Me: Feel free to connect with me on LinkedIn or drop me an email at [email protected].

  • πŸ˜„ Pronouns: He/Him

  • ⚑ Fun Fact: I'm an avid boulderer, conquering rock faces and challenging bouldering problems whenever I can. πŸ§—

Thanks for stopping by! Feel free to explore my repositories and don't hesitate to reach out for collaborations or discussions. Let's build something awesome together! πŸš€

D Tripp's Projects

booker icon booker

Recommendation Engine for Books

booker_ icon booker_

application for progress tracking in book reading.

codechef-nlp icon codechef-nlp

Topic Modeling and Natural language processing on problem statements and solutions provided by codechef competitive programming site

deeprl_algorithms icon deeprl_algorithms

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

fstream icon fstream

A minimalistic text-based social media platform with broadcasting of ephemeral messages

maze-similarity icon maze-similarity

Given a series of mazes encoded as zeros and ones, it was determined which two of the mazes were least similar. To solve, the mazes were converted into graphs and traversed using a depth first search, resulting in a sequence of directions. Sequence similarity was analyzed by evaluating each pair of sequences using a dynamic programming algorithm to find the maximum common subsequence. Of these results, the two mazes with the lowest similarity score were chosen.

minesweeper icon minesweeper

An ancient logic game which has been stumping puzzle lovers since 1992. We have coded a logical agent to play (and win) this game. As the agent uncovers squares, it builds a knowledge base and makes inferences about which squares are safe and which squares contain mines. As the agent examines the safe squares, more areas are opened. Sometimes, the agent is unable to determine whether a square is safe or not. In the case, advanced tactics for a probabilistic treatment of forced guesses are employed.

minima icon minima

Minima is a one-size-fits-all Jekyll theme for writers.

mountaincar-v0 icon mountaincar-v0

Mountaincar is a simulation featuring a car on a one-dimensional track, positioned between two β€œmountains”. The. Goal is to drive up the mountain on the right; however, the car’s engine is not strong enough to scale the mountain in a single pass. Therefore, the only way to succeed is to drive back and forth to build up momentum.

n-queens icon n-queens

The N-Queens chess puzzle is the problem of placing n queens on an n x n chessboard such that no two attack each other. This puzzle was solved using two techniques: Local (Hill-Climbing) Search and a Genetic Algorithm. Local Search finds an optimal solution by systematically evaluating and moving the worst-placed piece to a better square. The genetic algorithm runs several problem instances in parallel and uses elements of randomness to discover a solution. Solved up to n = 14

parse-log icon parse-log

Production Grade Log-Parsing CLI Application. Employs unit testing, logging, and CI/CD.

system-design-primer icon system-design-primer

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

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