crjacinro

Serge Nino Martin Villasica's repositories

compose-path-finding

A simple path finding visualizer mobile app to demonstrate the use of Jetpack Compose UI toolkit in Android.

Language:KotlinMIT38 10

compose-snake-desktop

A simple Snake application to demonstrate the use of Compose for Desktop platform with Kotlin

Language:Kotlin13 10

kotlin-flow-demo

A sample repository to demonstrate the use of Kotlin Flow in an Android application

Language:Kotlin200

Android-CleanArchitecture-Kotlin

This is a movies sample app in Kotlin, which is part of a serie of blog posts I have written about architecting android application using different approaches.

Language:Kotlin100

Cleaner Compose is a visualization of a 2d grid cleaner who wants to clean the entire room. The catch is to avoid the walls and to clean all the possible areas reachable by the cleaner starting point.

Language:Kotlin1 10

basic-go-kit

Language:Go010

deep-jazz-generation-coursera

A programming assignment from Coursera's Deep Learning Specialization on LSTM.

Language:Jupyter NotebookMIT010

hackerrank-solutions

This is a repository that contains my own runnable solutions of random problems in the hackerrank platform.

Language:C++010

leetcode-easy-problems

Collection of solutions from Leetcode Top 10 Curated Easy Problems using Kotlin. Solutions were created using Test-Driven Development

Language:Kotlin010

machine-learning-stanford

Repository for the problems and my own solutions for the Machine Learning course from Stanford University (using the Coursera platform)

Language:MATLAB010

structure-and-interpration-mit

A collection of code snippets in LISP based on the MIT Open Courseware on Structures and Interpretations of Computer Programs.

Language:SchemeMIT010

compose-breakout

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coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

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