Exploring my new self by giving my next 100 days entirely to coding world
#Day 1 ->
Started developing a basic car racing game using pygame
#Day 2 ->
Changed plans.
Now developing a hurdle kind of game.
Spent the day in improvising and debugging previous code.
#Day 3 ->
Completed basic outlook of the game including scoring and increase in difficulty level.
#Day 4 ->
Read docs from official site and looked for upcoming projects.
#Day 5 ->
Improvised on the same game by creating starting menu.
#Day 6 ->
Wrapped up first game with sound effects and introduction of dark theme.
#Day 7 ->
Back to machine learning practice starting with logistic regression for classification problems.
#Day 8 ->
Diving deeper into basics of pandas module in python.
#Day 9 ->
First open source contribution to mozilla addons.
#Day 10 ->
Completed first lesson of udacity course on intro to data analysis.
#Day 11 ->
Going on with udacity course.
#Day 12 ->
Spent day setting up ssh key,token etc on github and setting up profile on linkdn and moziilian.
#Day 13 ->
Revisting old work to improvise
#Day 14 ->
Continuing with improvisation
#Day 15 ->
Understanding matplotlib
#Day 16 ->
Advanced matplotlib and basic seaborn
#Day 17 ->
Done with graphing and plotting
#Day 18 ->
Linear Regression Practice
#Day 19 ->
Logistic Regression Practice
#Day 20 ->
K-Nearest Neighbour classification practice
#Day 21 ->
Support Vector Machine practice
#Day 22 ->
Understanding basics of trees
#Day 23 ->
K-means Clustering
#Day 24 ->
Recommender System
#Day 25 ->
Principle Component Analysis
#Day 26 ->
Natural language processing
#Day 27 ->
Practice on Natural language processing
#Day 28 ->
Twitter Sentiment Analysis using NLP
#Day 29 ->
Another approach to same problem
#Day 30 ->
Submission made
#Day 31 ->
Started with datathon
#Day 32 ->
Improving score on twitter sentiment analysis
#Day 33 ->
Practicing on datasets
#Day 34 ->
On practice mode
#Day 35 ->
Wrapped up Twitter SEntioment Analysis
#Day 36 ->
Automated pipelines and data versioning
#Day 37 ->
Spent day setting up tensorflow environment
#Day 38 ->
Taking up new project
#Day 39 ->
Improvising same project
#Day 40 ->
Finetuning the model
#Day 41 ->
Onto final stage
#Day 42 ->
Finished project
#Day 43 ->
Gathering data
#Day 44 ->
Dataset and dataset
#Day 45 ->
Break from NLP
#Day 46 ->
Recommendation Engine
#Day 47 ->
Finally successful in setting up environment
#Day 48 ->
Tackling same issues
#Day 49 ->
Finishing recommender system project
#Day 50 ->
Halfway down and inclined towards deep learning for now
#Day 51 ->
Continuing with deep learning concepts
#Day 52 ->
Diving into Neural networks
#Day 53 ->
Practice on NN
#Day 54 ->
Tried Implementing newly learned techniques
#Day 55 ->
Practicing skills
#Day 56 ->
Understanding ANN
#Day 57 ->
Getting into CNN's
#Day 58 ->
Trying to deploy nn's
#Day 59 ->
Starting new project
#Day 60 ->
Continuing with same project
#Day 61 ->
Preparing excel sheet for analysis
#Day 62 ->
Web scrapping
#Day 63 ->
Same Project!!
#Day 64 ->
Improvisation
#Day 65 ->
Final stages
#Day 66 - 73 ->
Understanding convolutional neural networks in depth
#Day 74 ->
Looking up for some projects
#Day 75 ->
Internship work
#Day 76-77 ->
Building Resume
#Day 78 ->
Setting up environment
#Day 79 ->
Recording Audio using pyaudio
#Day 80 ->
Learning speech to text convertion using python
#Day 81 ->
Text to speech converter
#Day 82 ->
Implementing speech to text conversion
#Day 83 ->
Improved model
#Day 84 ->
Further modifications
#Day 85 ->
Speech to text game
#Day 86 ->
Started new project
#Day 87 ->
Completed EDA
#Day 88 ->
Completed the dataset with final submission
#Day 89 ->
Started reading research papers
#Day 90 ->
Another research paper
#Day 91 ->
New Project
#Day 92-96 ->
Completed project from kaggle competetion
#Day 97 ->
Another dataset
#Day 98 ->
Another project completeion..this one being the fastest
#Day 99 ->
Starting with ds
#Day 100 ->
Last day of this journey