awannaphasch2016 Goto Github PK

adaptivegraphstructureembedding

research # 2

aiknowledgewarehouse

[In-Progress] migrate Example/ and Notebook/ from all the projects to this.

awannaphasch2016

awannaphasch2016.github.io

awscovid19socialmediacralwer

using AWS to crawl data from social media site.

blockchain-community

content to educate newbie to advance member of blockchain community

cdkfaucovid19cralwer

checker_easyai

computational-ai-assignment-

corona

covid19trendprediction

cryptoexpertidentification

model that rank and score expert-crypto pair given length of prediction overtime.

curatedsharedknowledgedbase

deep-stock

Deep Learning for Stock Market

doom-emacs

An Emacs framework for the stubborn martian hacker

dotfiles

containing dotfiles setup.

dvc_basic

ref: https://www.youtube.com/watch?v=kLKBcPonMYw&ab_channel=DVCorg

easy-ai-examples-fixed

emacs-config

my doom emacs configuration

emot

Open source Emoticons and Emoji detection library: emot

ensemblestreamingnetworkclassification

examples

Example deep learning projects that use wandb's features.

faucovid19

gittest

guix-notes

This repo has moved to https://gitlab.com/pjotrp/guix-notes Notes on Guix

hugo-blog

kegra_gcn

learngo

lifelongproject

TLDR: I am building a project that allow you to continuously contribute back to the project whatever new things you have learned related to certain career path. (I choose data science related fields) This will allow me to incrementally improve upon the project. for more details see below. When learning new things, I have found myself building small one time projects. The problem with this approach is that small project cannot grow organically to become larger. As a result, I come up with a project that have this properties of growing organically from contributing new things I have learn by building smaller project. This naturally lead to the following question: what should be my life long project? I figure this out by research all of the jobs positions description related to a range of jobs that I am currently interested in and jobs that I can be easily transitioned from one to another. (data engineer, database manager, data warehousing, data science, data analysist, data architect. ) After a few week of digging, I figured out the life long project idea. The life long project idea for data science related fields must have the following components: Data Scrapper: data must be available online, and data must be frequently updated. Data Pipeline: data pipeline must be large enough, so I can use certain tools which only make sense for larger projects. Data Warehouse: ways to store unstructure data after data is scrapped. Database: ways to store structure data to be analyzed Data Analysis: use data to create report. (which will result in blog post or somethings.) Data science: The project must allow for "data driven" approach. This way, I can treat the project as Port and Adapter architecture where new technologies that I learn can be either adapter or port which only change implementation and does not need to interact with design + logic inside the main codebase. The project will follow best practices + carefully design/implementation choice. I mentioned about properties + component of data science life long project. Now what I am missing is I also needs a small team that will allow me to be better team members. This is the reason I created this post to see if anyone maybe interested in working with me. Ultimately, I want the project to allow for smaller team to work on different part of the project. For example, if you are interested in learning about data engineer, then you will get involving with building data pipeline. If you interested in data science, then you will get involve in using the data from database to analyze things. Please comment down below or dm me. I will give you more detail about the the full project. I am opened for questions, suggestion, and concerned.

lsp-mode

Emacs client/library for the Language Server Protocol