Name: Ajika Angelo
Type: User
Company: Aacom Labs
Bio: Frontend engineer passionate about tech writing and ML & DS. Seeking impactful collaborations. Excited to innovate and create!
Twitter: ajikangelo
Location: Kampala, Uganda
Blog: ajikadev.hashnode.dev
Ajika Angelo's Projects
List of references and online resources related to data science, machine learning and deep learning.
Weather app done in Jetpack Compose for the #AndroidDevChallenge 2021 ๐ฆ โ๏ธ. Neumorphism UI.
This is a private repo for all my Android Studio projects
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
For a youtube Tutorial
A Collection on all Jetpack compose UI elements, Layouts, Widgets and Demo screens to see it's potential
Curated list of Python resources for data science.
Machine Learning algorithms built from scratch for AMMI Machine Learning course
๐ฆ ๐๐ฒ๐ฎ๐ฟ๐ป about ๐๐๐ ๐, ๐๐๐ ๐ข๐ฝ๐, and ๐๐ฒ๐ฐ๐๐ผ๐ฟ ๐๐๐ for free by designing, training, and deploying a real-time financial advisor LLM system ~ ๐ด๐ฐ๐ถ๐ณ๐ค๐ฆ ๐ค๐ฐ๐ฅ๐ฆ + ๐ท๐ช๐ฅ๐ฆ๐ฐ & ๐ณ๐ฆ๐ข๐ฅ๐ช๐ฏ๐จ ๐ฎ๐ข๐ต๐ฆ๐ณ๐ช๐ข๐ญ๐ด
IBM Advanced Data Science Capstone Project
Jetpack Compose Playground
Firebase Chat Application written in Kotlin and Jetpack Compose using Android Studio Preview.
AR (Augmented Reading) for the meta llama 3 h4ckathon ๐ฆ
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Implementing a ChatGPT-like LLM from scratch, step by step
This repository includes all the machine learning work i have been doing in the course of the semester for the course unit: Machine Learnign and AI
Learn how to design, develop, deploy and iterate on production-grade ML applications.
MedUI
Try to Neumorphism in Android (Just experimental!! ๐งช)
This is a music player application for Android phones
Predict rainfall levels using regression ML models. Explore linear regression, decision trees, random forests and more for accurate forecasting. Ideal for environmental and agricultural applications.
Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison
Course notes for Data Science related topics, prepared in LaTeX
A compilation of technical writing resources
A To do app in Android Studio