Desired Position for Nighthawk Coders Content Creation Internship

I am applying for the ML study plan.

I have experience in working on machine learning models in most of my projects:

  • Titanic ML

  • Bakery ML model for cooking game

  • Stocks ML model for my final project (implements sorting and searching algorithms to enhance user interaction)

  • I am used to created clean UI interfaces (frontend) and connecting this to backend databases (SQL) which would store user information/input.

LinkedIn

Checkout my linkedin to see my projects, achievements, and extracurricular that enhance my knowledge in this field and aid me in being a valuable candidate:

LinkedIn

Introduction

Key Interests and Coding

Engineering

Robotics Projects:

  • Backend: Use Python for controlling hardware components, processing sensor data, and running machine learning models for robotics applications.

  • Frontend: Use JavaScript with frameworks like React or Vue.js to create a web interface to monitor and control your robots remotely.

  • Integration: Develop APIs (with Flask or Django in Python) to allow communication between your robotics hardware and web applications.

Video Games

Game Development:

  • Frontend: Use JavaScript with game development libraries like Phaser or Three.js for creating browser-based games.

  • Backend: Use Python with game engines like Pygame for logic, AI behaviors, and handling game states.

  • Full Stack: Create multiplayer games by developing a server in Python (using frameworks like Flask or Django) to handle real-time data and WebSockets for live interaction.

Sports

Statistical Analysis:

  • Data Collection: Use Python for web scraping and API consumption to gather sports data.

  • Data Analysis: Implement machine learning models in Python (using libraries like Scikit-learn or TensorFlow) to analyze team performance and make predictions.

  • Visualization: Use JavaScript libraries like D3.js or Plotly to create interactive and visually appealing dashboards displaying sports statistics.

Nature/Wilderness

Weather and Data Tracking:

  • Data Retrieval: Use Python to gather weather data from APIs (such as OpenWeatherMap) and process this data.

  • User Interface: Develop a user-friendly web application using React or Angular to display weather forecasts and collect user inputs about hiking trips and experiences.

  • Integration: Create a backend in Python to manage data storage (using databases like SQLite or PostgreSQL) and serve the data to the frontend.

Health

Fitness and Health Apps:

  • Tracking Apps: Use Python for backend services to store user data securely and handle authentication.

  • User Interface: Use JavaScript and mobile development frameworks like React Native to build cross-platform fitness tracking apps.

  • Machine Learning: Implement predictive models in Python to provide users with personalized health and workout recommendations.

Family/Friends

Smart Calendar App:

  • Backend: Develop a scheduling backend in Python, capable of integrating with external calendars (Google Calendar API).

  • Frontend: Use JavaScript frameworks like React to create an intuitive and responsive user interface.

  • Features: Implement features like automated time suggestions and notifications to balance work and free time.

Social Media and Messaging Platforms:

  • Messaging: Develop real-time messaging functionality using WebSockets in Python (Django Channels) and JavaScript (Socket.io).

  • User Interface: Create engaging and interactive interfaces with JavaScript frameworks.

  • Security: Ensure data privacy and security with proper authentication and encryption practices on both the frontend and backend.

Event Planning Tools:

  • Backend: Use Python for event management services, including invitations, RSVPs, and reminders.

  • Frontend: Develop easy-to-use interfaces with JavaScript for users to create and manage events.

  • Collaboration: Implement features for collaborative event planning and task management.

Online Multiplayer Games:

  • Game Logic: Use Python for server-side game logic and player state management.

  • User Interface: Use JavaScript with WebGL for graphics and interaction in browser-based multiplayer games.

  • Real-time Communication: Implement real-time communication between players using WebSockets.

Projects and Teamwork

Projects/Key Achievements

(All projects can be found under my LinkedIn)

Trimester 1 Passion Project

  • Got used to working in a development setting

  • Was my teams scrum master and worked on organizing plan/issues

Goal: Create an exotic car webpage that allowed users to rent cars and view information about respective cars

Result: Allowed user to view information and make reservation

Takeaways:

  • Frontend design was well organized and made

  • Backend functionality was lacking and needed improvement

  • Learned to create an API with endpoints that registered on the frontend

  • Teamwork lacked and needs for lots of improvement

  • Solid base to start working off of and experience in full stack development

Trimester 2 Binary Logic

  • Had a more functional team

  • Able to learn from more experienced team members

Goal: Create a ascii art generator based on rgb values of inputted image

Result: Outcome came out as expected and allowed user to customize which symbols were used in the ascii art

Takeaways:

  • Enhanced front end skills and became a lot more confident

  • Well rendered front end design

  • Learned effective styling with sass

Trimester 2 CPT Project

  • Introduced to SQL databases and CRUD

  • Implemented get, post, put requests in python flask api

  • Used javascript fetch requests to link frontend and backend together

Goal: Create a interactive cooking game similar to Little Alchemy called (Let E’m Cook)

Result: Achieved all our goals and surpassed them

Takeaways:

  • Good frontend design creating a sandbox, shop, friends list, and trading system

  • Extensive planning throughout development

  • Great collaboration and successful project

  • Well organized backend, good code commenting, and issues that outlined project progress

Trimester 3 Data Structures

  • Implemented ML models in backend databases

  • Worked off of Titanic ML template

Goal: Get the titanic model to work, and then start working on a custom ML model

Result: Got Titanic model to work in well rendered frontend and creating a Baking ML model that predicted item purchased from time

Takeaways:

  • Understood how to implement ML models in Flask apis

  • Learned to filter data used in ML models/CSVs

  • Somewhat understood linear regression, random forest, and other ml algorithms used in programs

  • Added ML Bakery in my CPT project and built off it

Trimester 3 Final Project

  • Combined learnings of all projects to help add to team members feature

Goal: Research sorting and searching algorithms to implement in a stock database to sort data by date, sectors, and allow users to purchase stocks.

Result: Worked with teamember Varun, and achieved a desirable final product

Takeaways:

  • Researched a looked into bubble, merge, and bucket sorting algorithms for the program.

  • Implemented merge and bucket sorting

  • Used SQL database for stock data, and filtered CSV file to implement sorting and match values in the database

  • Kept existing features and graph display of stocks

  • Added more functionality and organization to feature

Teamwork Methodologies and Artifacts

Agile Methodology

  • Consists of a cycle of coordination and documentation that involves various practices and principles…

Core Principles

  • Individuals and interactions over processes and tools

  • Working software over comprehensive documentation

  • Responding to change over following a plan

Key Practices

  • Sprints: short, time-boxed iterations (typically 1-4 weeks) to develop and deliver usable software

  • Daily standup’s: brief, daily meetings to discuss progress, plans, and impediments

  • Continuous integration: regularly integrating code changes into a shared repository

Application

Integrated in my own experiences with teamwork planning and work organization for efficiency, communication with one another and receiving feedback and revising accordingly to produce the most valuable work possible

Ideation/Planning

Consists of planning based off of given circumstances…

Core Principles/Key Practices

  • Goal-setting: clearly define objective

  • Research and analysis: gather relevant info and analyze current conditions, constraints, opportunities, etc.

  • Strategy development: establish strategies and approaches to achieve the goals

  • Task identification: break down strategy into specific tasks and activities

  • Timeline creation: develop a schedule/day-by-day plan with deadlines/milestones

  • Monitoring and adjustment: implement the plan and regularly review progress, making adjustments as needed

Application

Implemented in my own work with teams in creating various GitHub issues and blogs to plan work and ideate solutions to problems, establishing a foundation for work that would follow

Proof of Participation

github

Commits:

Introduction of Full Stack Coding Skill Set and ML Experience

Full Stack Coding Skill Set

Throughout the year in AP Computer Science Principles, I have developed a solid full stack coding skill set. On the backend, I have worked extensively with Python and Flask to create and manage API endpoints, handle server-side logic, and manage data using SQLite databases. On the frontend, I have become proficient in HTML and JavaScript, building dynamic web pages and user interfaces. I have also developed machine learning algorithms to generate optimal outputs based on user inputs. Additionally, I have learned to organize development using Agile methodology and effective planning strategies. This diverse skill set has equipped me to build complete web applications and understand various aspects of digital development. In addition my understanding of the internet and processes that occur on the web have improved. I’ve learned to be successful in deployment and other valuable development skills.

Machine Learning (ML) Experience

I engaged in machine learning projects that applied various algorithms to address practical problems. One significant example involved creating a predictive model for Titanic survival using Python and Seaborn for data analysis and visualization. By leveraging the Logistic Regression algorithm, we trained the model to estimate survival probabilities based on passenger attributes such as gender and age. Additionally, we developed an algorithm to predict bakery item orders using historical data stored in a CSV file. For these predictions, we utilized Linear Regression. After preprocessing data with Pandas, we employed the Decision Tree Classifier to predict the likelihood of specific bakery items being ordered at different times. This involved feature engineering, where factors like time, day type (weekday/weekend), and part of the day (morning/afternoon) were extracted and used as inputs. Using Scikit-Learn’s libraries for model training and evaluation, we applied our understanding of algorithmic techniques, data manipulation, and predictive modeling. For my final project, we created our own “ml model” that used sorting algorithms to filter stock data to benefit users using the app. It required skills learned from previous projects like filtering/formatting data, initializing a payload, api endpoints, and fetch requests to work. Overall, these ML projects were crucial in enhancing my understanding of predictive algorithms and contributed significantly to my accomplishments as a Full Stack Developer.

Showcasing Projects:

N@tM - Trimester 1

  • Presented “Passion Project” at N@tM with my group
  • Exotic Car Renting Web Page
  • Attracted a good amount of attention during our presentation time, with students and parents alike coming to see other try renting cars, experiencing our 3d blender car garage, and viewing car information.

N@tM - Trimester 2

  • Presented “CPT Project” at N@tM with my group
  • Contributed to group presentation by presenting my feature, demonstrating the coordination of leaderboard and point update that showed up after baking an item for each user
  • More interesting project, attracted more people
  • Improved presentation skills

N@tM - Trimester 3

  • Presented “Final Project” with my group
  • Stocks sorting algorithms and UI that allowed people to buy stocks was well rehearsed and effectively displayed to those watching
  • Made a greater impact on my audiences than before presentations

Favorite Project Demo

My favorite project I would like to demo is my cooking game Let E’m Cook which I spent the most time and effort on perfecting and improving for the collegeboard CPT assessment. I made major improvements i=on the project throughout the year and it would be the best one to demo and show my ability as a full stack developer. Would like to implement a more practical ML model that would make the game more interesting.

Unique Qualification(s)

Throughout the year, I have demonstrated my abilities as both a programmer and student when organizing, planning, and executing group projects. Additionally, as a leader, I asked clarifying questions that benefit the group, outline teacher/group expectations, and managed workflow as the Scrum Master.

  • Hard worker that perseveres through problems

  • Strategic planner with good attention to detail

  • Ability to foster collaboration, cooperation, and creativity within a team

  • Provide guidance, support, and motivation to rest of the team

My experience from this year was valuable in establishing myself as a group leader and programmer in a development setting. My interests lie in exploring machine learning models and AI. My learnings in full stack development and ML have helped me excel in this class and make me capable and worthy for a position in Nighthawk Coders Content Creation internship under the ML Study Plan.