Software I use, frameworks I love, and other things I recommend.

I get asked a lot about the things I use to build software, stay productive, or libraries I use in order to do some programming. Here’s a big list of all of my favorite stuff.

Main Tech stack

  • Firebase

    I am most comfortable in using Firebase as a backend for quickly finishing projects.

  • Google Cloud Run

    I believe that serverless is the best way in deploying your products, Google Cloud Run never fails me in doing so.

  • Flask

    Flask is one of the easiest ways for me to do some logic behind my code as I am most comfortable in Python as my programming language. Flask is my go-to way in making a Rest API.

  • Tailwind CSS

    TailwindCSS makes the frontend design for me as a developer, exponentially easier. There are a lot of Tailwind CSS frameworks available for use and it takes the responsibility of naming arbitrary classes from me.

Programming Languages

  • Python

    As a Data Engineer, I use Python extensively for data cleaning, analysis, and automation. Leveraging libraries like pandas and numpy, I streamline data processing and employ machine learning frameworks such as tensorflow and Scikit-learn to build predictive models.

  • C

    I view C as a starting point. C programming help me understood the basics of programming. A lot of programming languages and tools were built on top of C and I think it is crucial to know C in order to be a great programmer.

  • R

    In my role, I employ R for statistical analysis and data visualization, using libraries like dplyr and ggplot2. It helps in creating detailed reports and insights from complex datasets, enhancing decision-making processes.

  • JavaScript

    I use JavaScript to develop interactive data dashboards and front-end interfaces, enabling real-time data visualization and user interaction with data-driven applications. This facilitates easier data exploration and accessibility for stakeholders.

Frameworks/Libraries

  • Python & R Libraries

    Pandas, numpy, tensorflow, Scikit-learn, pytorch, matplotlib, seaborn, flask, Gradio, Stable Baselines, Keras, dplyr

  • API Dev and Version Control

    REST API, Git, Github, openai API, and many more LLM APIs

  • Frontend Frameworks

    React, TailwindCSS, HTML, Bootstrap

  • Backend Tools

    Firebase, SQL, MySQL

  • Low/No Code Tools

    Airtable, Make, Zapier, Softr, Wordpress

Google Cloud Products

  • Cloud Run

    I use Google Cloud Run to deploy and manage scalable data processing services and APIs. This allows for seamless handling of data workloads, ensuring efficient processing and availability of data-driven applications.

  • Cloud Storage

    I utilize Google Cloud Storage for storing large volumes of raw and processed data. It provides a reliable and secure solution for data backup, archival, and access, facilitating smooth data retrieval for analytics and machine learning tasks.

  • Big Query

    I leverage BigQuery for performing large-scale data analysis and complex queries on massive datasets. It helps in generating actionable insights through efficient and quick processing of data, supporting data-driven decision-making.

  • Google APIs & Services

    Google Sheets API, Youtube Data API, Solar API

Certificates

  • Mathematics for Machine Learning

    By Imperial College London
    Skills: Machine Learning, Linear Algebra, Statistics

  • Stanford Machine Learning Course

    By Stanford University
    Skills: Reinforcement Learning, Machine Learning, Deep Learning

  • Data Analysis with R Programming

    By Coursera
    Skills: Data Analysis, R (Programming Language)