Plan

April

Book recommendation system

• implement Classify API

Data Structures

• Drill through all the easy problems + start medium level ones

Web Development theory

• The Odin Project + Mozilla documentation on web development fundamentals + server-side in depth

Done

March

Book recommendation system

• set up Django Backend
• implemented an external API to see if backend setup will work with the Classify API

Data Structures

• Practice problems on AlgoExpert

Breads

• set up local development
• solved CORS issue
• set up basic pagination (featured is not being implemented in the end)
• learn JavaScript through the Odin Project to be able to contribute to this project

February

Book recommendation system

• Django tutorials - Corey Shafer
• set up Django Backend for [[Book recommendation system]]

CIS Collegiate Independent Study Website

• Spring -> Django Migration
• run python script from Spring
  • test case hello.py file
  • return log.txt which is the output from ProcessBuilder java class

January

Open University

• move nested books from /category to /category?expand=book
  • remove nested books from /category entirely
  • bookcategory/4,5,6 to see all books within these categories
• how to batch upload books for POST method
• create a bookcategory_id to generate unique ids
• update database schema to show how backend works

Data Structures

• Chapter 5 - Runestone Book
• algo expert - 20 questions completed

December

CIS website

• set up mySQL locally
• upload script and create a username to access data
• create Subcategory table
• set up Postman
• add data to books table
• test out Bing's code
• figure out contribution in github (git theory)
• create User table + all it's properties
• Work with (front end) for User-history API
• pull from deploy and test
• simplify database with Category <--> Book relationship (Many to Many)
• Create relationship User <--> User history (Many to Many)
• generate Mock data using a Python webscrapper

November

Intelligent Document Classifier

• Deploy app on server
  • execute jar file
• learn spring boot
• fix bugs on intelligentdocumentclassifier for the back-end part
  • No bugs
• connect with front end to migrate intelligentdocumentclassifier to new angular uploader which will replace http://66.76.242.198/.
  • Completed more effectively by someone else on the team
  • My work still needed to deploy both front and back end separately to connect the two

Python - Data Structures

• Theory: Codebasics - Data Structures & Algorithms in Python playlist
  • went through all major concepts through the Python DS book

October

• Volunteer Project
  • python data extraction
  • [[Java]] uploader
    • Maven
    • Spring
    • Angular (run)
• Practice: Tiny Python Projects book: 1st half
• Practice: Thredup project
  • Inputs
    • url
    • number of pages
    • file name
  • use classes?
• Install Docker
  • Docker Compose
• upload to Github
  • Learning Plan
  • Data Structures exercises
  • Tiny Python projects - my solutions

September

Week 4: HackerRank Conference

• Codebasics - Data Structures & Algorithms in Python get started on playlist

Week 3: ODSC

• Learn what these do
  • GCP
  • Azure
  • AWS
  • Spark
• Python gaps
  • classes (learning through Linked Lists practice)
• ODSC Conference Thursday + Friday
  • resume for career fair - Saturday

Week 2: SQL + job applications

• apply to jobs + internships
• SQL refresher - Data36
• Leetcode practice - Python
• ODSC scholarship application
• ODSC registration for all events

Week 1: Thredup database

• organize all files according to How to Organize Your Data Science Project
• basic webscrape COMPLETED!
• scrape ~1000 items
• Clean up all code

August

Week 2-4: Thredup Database

• created a kanban board - all todos have migrated to the github project page
• Updated README file on Github for latest todo

Week 1: Thredup Database

• Thredup project
  • clean-up Obsidian notes
  • create a copy of a Github folder that syncs md file with Obsidian's file (don't want to keep copies at two locations
  • push to Github (code + md notes)
• Anki
  • Git cards - push, pull, etc.
• Website
  • fix site
  • ideas: menu, posts, layout
• Org-Roam
  • Test out 2nd Org-Roam installation on separate conda environment
  • Guide to Installation: complete
• Linux
  • Anki
  • conda env for thredup project
  • update migration to Linux page

July

Week 5: Thredup Database

• Thredup up project
  • finish all functions
  • rest of the functions to be used later - also worked on them
• Dual Boot Laptop - oh boy!
• Figure out environments: conda and homebrew
  • Experiment with installations with homebrew, then conda on other Linux distro - didn't use conda

Week 4: Thredup database

• Thredup Webscrape:
  • links
    • combine links with href header: thredup.com
  • split urls for different clothing categories
  • realized: cannot scrape for categories within "all petite" items
  • multiple functions
• DS setups + those who do both DS + side projects

Week 3: Debug + Environments

• Work on Thredup Page
  • ideas: entire python library + build database using all petite items
  • web scrapper for pulling non-polyester items stopped working
  • web scrapper for pulling 100% linen items - use database instead
  • web scrapper for building a database start
    • pull links for the main pages - won't work with bs4, due to website layout. Not all href's are able to be pulled + random hrefs for products get pulled. Need to you XML formatting
      • yank all hrefs/page - not anymore
      • selenium to move to the next pages - not anymore
• Get Doom Emacs
• Purchase computer accessories for working at home
• Acer One laptop:
  • attempt clean-up
  • wipe out system

Week 2: Anki + Feynman technique

• Fix thredup code
• move over any "Spotify Project" related files from host to guest OS
• move over simplified version of Digital Ocean files
• debugging
  • VS Code - general debugging
  • Python debug configurations in Visual Studio Code
• Digital Ocean:
  • sort through all files
  • organize
  • download
  • delete - will cancel credit card
• LinkedIn - update all work description
• Feynman | DS concepts for Classification:
  • AUC curve
• Feynman | DS concepts for Regression
• create a map for all concepts so far + tangents to see what directions I've been going in
• start Thred-up ML project - 1 hour
• start community involvement project
• Anki: map, filter, reduce and lambda:
  • definition
  • syntax
  • example

Week 1 (3 days): Anki + Feynman

• Anki | python code in DS | 20 cards
• Feynman | DS concepts for Classification:
  • Confusion Matrix
  • Accuracy
  • Precision & Recall
  • F1 Score
  • Harmonic Mean (from F1 score)
  • F$\beta$-score (from F1 score)
  • Sensitivity & Specificity
  • ROC Curve

June

Week 5 - 2 days:

• Ultralearning review + update (mid year evaluation)
• Notes | scikit learn

Week 4:

• download RESULTER extension for google search shortcuts
• increase storage again - new way for Ubuntu 20.04
• reinstall Ubuntu after expanding hard drive mistake
• VS code: basic debugging
• VS code won't run Python - how to enable?
• access shared folder between host and guest systems
• Ideas vomit for open source projects: education (The Prize), government, businesses (Amazon → buying locally) Open Source Projects
• Will Athens be using Emacs? - nope
• change default environment to DJ-set - don't think you can

Week 3: Set up local machine - Ubuntu setup + Remixatron

• delete XUbuntu
• Install Ubuntu
• Install VirtualBox Guest Additions - automatically adjust resolution (to match host) + shared clipboard and drag and drop between host and guest systems
• Slow Ubuntu - wrong ISO mounted, reinstalled just incase
• Install miniconda + conda onto Virtual Box
• create environment
• Organize environments + GitHub folders problem arose from VS Code not being able to find pydub (installed in a different folder using conda than where pip was installing)
• no longer use Spotify's API
• run Remixatron on command line - won't run because of pygame
• embed client ID into jupyter notebook
• audio analysis (audio from youtube) using Spotify's API
• identify beat breakdown for Daechiwita + DNA. Didn't work since I was downloading music from YouTube and using Spotify's analysis on it
• switch from jupyter lab to VS Code VS code can run notebooks!
• widget for jupyter notebook to play 2 audio samples (downloaded from youtube?)

Week 2: Research into 'Daechwita —> DNA' project + VMs (using Linux fully)

• created separate page for the 'Daechwita —> DNA' project
• beats and tempos match! extracted from dict in analysis
• most code uses javascript with html + css (makes sense) with the spotify API
• discovered lots of resources, for python as well
• The Autocanonizer source: youtube
• Spotify audio analysis source: spotify track plays locally on desktop while song bar progresses on the web browser
• EternalJukebox - better README notes + is more updated than autocanonizer
• Youtube-dl - command-line program to download videos from YouTube.com and a few more sites
• Discovered Remixatron on AlternativeTo
  • forced myself to learn git to download and play around on the command line
• Virtual box vs. SSH?
• Remixatron is giving array allocation errors. Code it myself!

Week 1: Led Zeppelin Project

• Led Zeppelin project - documentation
• Led Zeppelin project - define objective
• pull + sort albums from given artist

May

Week 4: Blog posts + interview questions

• Interview questions - 1 hour per day
• Data Science assignment
• How to solidify Python?

Week 3: Job applications

• redirect URL to notion or redirect from WordPress site itself
• Create word/pdf resume
• search for jobs
• cover letters
• job applications

Week 2: Online presence

• Website
• Resume
• Portfolio
• Completed Complete Machine Learning and Data Science: Zero to Mastery on Udemy.
  • Time: 1 month to complete
  • Also understand Python fundamentals better
• organize DS/ML documentation - majority

Week 1: Finish Python section of course

• Python videos - basically finishes up the whole course

April - back home in Quarantine

• Worked on Machine Learning and Data Science: Zero to Mastery on Udemy.
• Learned Github fundamentals - create respositories, push, pull
  • Edited projects + updated profile
• Updated LinkedIn
• started working on website and resume
• organized all notes

March - Sri Lanka

• Discovered new resources on 3/25/20:
  • The Beginner’s Guide to Kaggle
  • The Ultimate Python Seaborn Tutorial: Gotta Catch ‘Em All
  • Python Machine Learning Tutorial, Scikit-Learn: Wine Snob Edition
  • How to Learn Machine Learning
• Titanic data - completed seaborn (graphing + plotting) + SciKit (machine learning model, random forests)
• Looked at “titanic-start-here-a-gentle-introduction” on kaggle and didn’t understand the statistics (Logistic Regression)
• Discovered on YouTube: Daniel Bourke’s code with me and codebasics’ machine learning playlist (learned about logistic regression)

February - Bangalore

• Statistics for Data Science | Probability and Statistics - for overview/introduction
• Completed Probability and Statistics for Business and Data Science on Udemy.
  • Time: 1 week to complete
• Pull Spotify features + analysis from Spotify's API using spotipy
• Thredup webscrapping python code
• Real Estate webscrapping python code

2019

• Python - Automate the boring stuff (first half of Udemy course)
• The Odin Project - started it off
• Data 36 - SQL practice
• Codewars - python + SQL practice
• SQL - interview questions