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https://github.com/hithesh111/Hith100

My 100 Days of ML Code Challenge Repository. Note: I stopped updating in the blogger site. The days after 100 days are documented in another repository.
https://github.com/hithesh111/Hith100

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My 100 Days of ML Code Challenge Repository. Note: I stopped updating in the blogger site. The days after 100 days are documented in another repository.

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100 Days of ML (100% completed)


Dec 3, 2019 to 11 Mar, 2020

Beyond 100 Days Repository : https://github.com/hithesh111/HithBeyond100

Covered:



  • Machine Learning (Coursera course by Andrew NG)

  • Feature Engineering (How to Win a Data Science Competition course by National Research University Higher School of Economics)

  • Tree Based Models (Statquest Youtube Channel by Josh Starmer)

  • Data Competitions (Regression, Classification problems on Kaggle and Hackerearth)

  • Deep Learning (4 courses in the Deep Learning Specialization by deeplearning.ai)


    • Neural Networks and Deep Learning

    • Deep Neural Networks: Hyperparameter Tuning, Regularisation and Optimisation

    • Structuring Machine Learning Projects

    • Convolutional Neural Networks




  • Data Visualisation using Seaborn (Data Talks Youtube Channel)

  • Intro to Tensorflow for Deep Learning (Udacity course)

  • NLP (till Week 13 of Stanford NLP course by Jurafsky)

Languages, Tools and Libraries familiarised:



  • Python

  • Numpy

  • Pandas

  • Seaborn

  • Scikit-learn

  • NLTK

Note: All the resources used are available for free on the internet.

Highlights (Mini-projects, Implementations, Illustrations and Competition Submissions):



  • K-Means Clustering (FIFA 19 Dataset) - Day 4

  • Anomaly Detection (Credit Card Transaction Fraud Detection) - Day 7

  • Kaggle House Price Prediction Competition - Day 18

  • Linear Regression from Scratch - Day 27

  • Logistic Regression from Scratch - Day 34

  • Polynomial Regression from Scratch - Day 36

  • HackerEarth Airplane Accident Severity Challenge - Days 39,62,63,67

  • Kaggle Titanic Disaster Survival Challenge - Day 40

  • Data Visualization using Seaborn Library - Days 44-53

  • Simple Neural Network using Tensorflow - Days 64

  • Image Augmentation and Classification - Day 71

  • Text Classification using NLTK - Day 81

  • Preprocessing, POS Tagging, Chunking - Day 96

  • Chat vs Article Text Classifier - Day 99

Day 1 - Linear Regression, Logistic Regression and Neural Networks.

3rd December
Revised Week 1 to Week 4 of Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day001.ipynb

Day 2 - Backpropagation, Error Analysis, Bias and Variance

4th December
Revised Week 5 and Week 6 of Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day002.ipynb

Day 3 - Support Vector Machines

5th December
Revised Week 7 of Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day003.ipynb

Day 4 - K-Means Clustering (with FIFA 19 Dataset Project)

6th December
Revised Clustering from Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago and worked on FIFA 19 dataset to cluster a set of football players (using FIFA 19 in-game stats) into 4 classes expecting the clusters to reflect on the position,style and quality of play.
Project: https://github.com/hithesh111/Hith100/blob/master/fifa19playerclustering.ipynb

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day004.ipynb

Day 5 - Principal Component Analysis (PCA)

7th December
Revised Dimensionality Reduction and Principal Component Analysis from Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day005.ipynb

Day 6 - Anomaly Detection

8th December
Revised Anomaly Detection from Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago and started working on Credit Card Transaction Dataset to detect fraudulent transactions.

More: https://hitheshai.blogspot.com/2019/12/100-days-challenge-day-6-anomaly-detection-credit-card-fraud-project.html

Day 7 - Anomaly Detection (Credit Card Fraud Transactions Project)

9th December
Completed the Credit Card Fraud Detection Project using Anomaly Detection algorithm.

Project: https://github.com/hithesh111/Hith100/blob/master/creditcardfraud.ipynb

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day007.ipynb

Day 8 - Recommender Systems

10th December
Revised Recommender Systems from Week 9 of Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day008.ipynb

Day 9 - Gradient Descent with Large Datasets, Online Learning, Photo OCR

11th December
Revised Gradient Descent with Large Datasets, Online Learning, Photo OCR from last two weeks of Andrew Ng's Machine Learning course on Coursera which I had already completed a few months ago.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day009.ipynb

Day 10 - Decision Trees and Random Forests

12th December
Learnt about Decision Trees and Random Forests from StatQuest Youtube channel

More: hhttps://github.com/hithesh111/Hith100/blob/master/100Days/day010.ipynb

Day 11 - Days 1 - 10 Review and Quizzes

13th December
Took quizzes on few topics covered in days 1-10, filled gaps in understanding certain concepts, cleared some doubts and found some new and related information.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day011.ipynb

Day 12 - Regression Trees

14th December
Learnt about Regression Trees from StatQuest YouTube Channel

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day012.ipynb

Day 13 - Gradient Boost

15th December
Learnt about Gradient Boosting from videos on Statquest Youtube channel

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day013.ipynb

Day 14 - Datasets and Feature Engineering

16th December
Learnt feature engineering methods from Krish Naik's Youtube channel and videos from How to Win a Data Science Competition Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day014.ipynb

Day 15 - Kaggle House Price Prediction Competition Part 1

17th December
Entered House Price Prediction Competition on Kaggle and tried various methods of preprocessing the data and selecting features learnt yesterday.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day015.ipynb

Day 16 - Kaggle House Price Prediction Competition Part 2

18th December
Found and created more meaningful features and tuned Random Forest thresholds. Best submission gave a MSE of log error value of 0.15600 and was ranked 3729/5775.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day016.ipynb

Day 17 - Kaggle House Price Prediction Competition Part 3

19th December
Tried to tune the random forest and played around with the Random Forest parameters even more. Tried Gradient Boost. Made very slight progress in the score (0.15522)

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day017.ipynb

Day 18 - Kaggle House Price Prediction Competition Part 4 (Summary)

20th December
Tried encoding various variables according to how they correlate with the SalePrice and played around with Linear Regression and GradientBoosting parameters. Made slight progress and jumped few steps on the leaderboard.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day018.ipynb

Code: https://github.com/hithesh111/Hith100/blob/master/house_price_competition_kaggle.ipynb

Day 19 - San Franscisco Crime Classification Competition Part 1

21st December
Started working on Kaggle San Francisco Crime Classification competition.

More: hhttps://github.com/hithesh111/Hith100/blob/master/100Days/day019.ipynb

Day 20 - San Franscisco Crime Classification Competition Part 2

22nd December
Tried to modify the data to create useful labels for the model.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day020.ipynb

Day 21 - Deep Learning Prerequisites

23rd December
Skimmed through Part I (prerequisites for rest of the book) of Ian Goodfellow's Deep Learning book at deeplearningbook.org

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day021.ipynb

Day 22 - Neural Networks and Deep Learning W1

24th December
Watched videos of Week 1 of Neural Networks and Deep Learning by deeplearning.ai on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day022.ipynb

Day 23 - Neural Networks and Deep Learning W2

25th December
Watched videos of Week 2 of Neural Networks and Deep Learning by deeplearning.ai on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day023.ipynb

Day 24 - Neural Networks and Deep Learning W3

26th December
Watched videos of Week 2 and Week 3 of Neural Networks and Deep Learning by deeplearning.ai on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day024.ipynb

Day 25 - Neural Networks and Deep Learning W4

27th December
Watched videos of Week 4 of Neural Networks and Deep Learning by deeplearning.ai on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day025.ipynb

Day 26 - Deep Neural Network Implementation

28th December
Tried implementing a deep neural network with 4 layers to approximate complex functions added with normally distributed noise.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day026.ipynb

Day 27 - Linear Regression from Scratch

29th December
Implemented Linear Regression using Gradient Descent using only numpy matrix operations.

Code: https://github.com/hithesh111/Hith100/blob/master/100Days/day027.ipynb

https://github.com/hithesh111/Hith100/blob/master/linear_regression_gradient_descent.ipynb

Day 28 - Regularization of Deep Neural Networks

30th December
Watched some videos from Week 1 of Hyperparameter Tuning, Regularization and Optimization course which is Part 2 of Coursera Deep Learning Specialization on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day028.ipynb

Day 29 - Exploding weights and Gradient Checking

31st December
Watched remaining videos from Week 1 of Hyperparameter Tuning, Regularization and Optimization course which is Part 2 of Coursera Deep Learning Specialization on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day029.ipynb

Day 30 - Mini-Batch Gradient Descent, Exponentially Weighted Averages

1st January 2020
Watched videos from Week 2 of Hyperparameters, Regularization and Optimization Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day030.ipynb

Day 31 - Tuning Process

2nd January
Watched some videos from Week 3 of Hyperparameters, Regularization and Optimization Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day031.ipynb

Day 32 - Batch Normalization

3rd January
Watched some videos from Week 3 of Hyperparameters, Regularization and Optimization Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day032.ipynb

Day 33 - Softmax Classifier

4th January
Watched remaining videos from Week 3 of Hyperparameters, Regularization and Optimization Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day033.ipynb

Day 34 - Logistic Regression from Scratch

5th January
Implemented Logisic Regression using only numpy matrix operations.

https://github.com/hithesh111/Hith100/blob/master/100Days/day034.ipynb
Code: https://github.com/hithesh111/Hith100/blob/master/Implementations/logistic_regression_from_scratch.ipynb

Day 35 - Metrics and Train/Dev/Test Split

6th January
Watched some videos from Week 1 of Structuring Machine Learning Projects Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day035.ipynb

Day 36 - Polynomial Regression from Scratch

7th January
Implemented Polynomial Regression using only numpy matrix operations.

Code: https://github.com/hithesh111/Hith100/blob/master/100Days/day036.ipynb

Day 37 - Human Level Performance and Bayes Error

8th January
Watched remaining videos from Week 1 of Structuring Machine Learning Projects Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day037.ipynb

Day 38 - Error Analysis

9th January
Watched videos from Week 2 of Structuring Machine Learning Projects Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day038.ipynb

Day 39 - HackerEarth Airplane Accident Severity Challenge

10th January
Participated in Airplane Accident Severity Classification Challenge on Hackerearth, made submission. Competition ends on 9th February. Currently 17th out of 520 on the leaderboard. Will upload the code once the competition is over.

Competition Details and More: https://hitheshai.blogspot.com/2020/01/100-days-of-ml-day-39-hackerearth-airplane-accident-severity-challenge.html
https://github.com/hithesh111/Hith100/blob/master/100Days/day039.ipynb

Day 40 - Kaggle Titanic Disaster Survival Challenge

11th January
Participated in Titanic Survival Classification Challenge on Kaggle. Currenly top 18% on the leaderboard.

Code: https://www.kaggle.com/hithesh111/kernel13c856e03f?scriptVersionId=26695158
https://github.com/hithesh111/Hith100/blob/master/100Days/day040.ipynb

Day 41 - Data Mismatch

12th January
Watched videos from Week 2 of Structuring Machine Learning Projects Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day041.ipynb

Day 42 - Transfer Learning, Multitask Learning and End to End Learning

13th January
Watched remaining videos from Week 2 of Structuring Machine Learning Projects Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day042.ipynb

Day 43 - AdaBoost

14th January
Watched a video about AdaBoost Model Course on StatQuest Channel on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day043.ipynb

Day 44 - Seaborn: Distplots and KDE

15th January
Watched a video about Distplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day044.ipynb

Day 45 - Seaborn: kdeplots

16th January
Watched a video about kdeplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day045.ipynb

Day 46 - Seaborn: pairplots

17th January
Watched a video about pairplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day046.ipynb

Day 47 - Seaborn: stripplots and swarmplots

18th January
Watched videos about stripplots and swarmplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day047.ipynb

Day 48 - Seaborn: boxplots and jointplots

19th January
Watched videos about boxplots and swarmplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day048.ipynb

Day 49 - Seaborn: violinplots

20th January
Watched a video about violinplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day049.ipynb

Day 50 - Seaborn: lmplots

21st January
Watched a video about lmplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day050.ipynb

Day 51 - Seaborn: pointplots, barplots, countplots

22nd January
Watched a video about pointplots,barplots and countplots on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day051.ipynb

Day 52 - Seaborn: catplots,heatmaps

23rd January
Watched videos about catplots,heatmaps on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day052.ipynb

Day 53 - Seaborn: tsplots,boxenplots,facetgrid

24th January
Watched videos about tsplots,boxenplots,facetgrid on Seaborn from Data Talks Youtube Channel and played around with important parameters.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day053.ipynb

Day 54 - Convolutions and Edge Detection

25th January
Watched lectures from Week 1 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day054.ipynb

Day 55 - Layers in CNN

26th January
Watched lectures from Week 1 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day055.ipynb

Day 56 - Classic CNN Architectures and ResNets

27th January
Watched lectures from Week 2 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day056.ipynb

Day 57 - Inception Networks, Transfer Learning, Data Augmentation

28th January
Watched lectures from Week 2 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day057.ipynb

Day 58 - Object Localization and Landmark Detection

29th January
Watched lectures from Week 3 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day058.ipynb

Day 59 - YOLO Algorithm

30th January
Watched lectures from Week 3 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day059.ipynb

Day 60 - Face Recognition

31st January
Watched lectures from Week 4 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day060.ipynb

Day 61 - Neural Style Transfer

1st February
Watched lectures from Week 4 of Convolutional Neural Networks Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day061.ipynb

Day 62 - HackerEarth Airplane Accident Severity Challenge

2nd February
Improved the score and rank in the Airplane Accident Severity Classification Challenge on Hackerearth, afer understanding the data better, doing better preprocessing and finding sweet spot of model parameters. Jumped from rank 330 (94.3 percentile) to 104 (98.2 percentile) on the leaderboard.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day062.ipynb

Day 63 - HackerEarth Airplane Accident Severity Challenge

3rd February
Since many features roughly follow normal distribution(observed using plots) I tried using multivariate normal pdf to predict which of the four severity does the accident most likely belong. But results were terrible even on the training set(42% accuracy). No improvements on the leaderboard.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day063.ipynb

Day 64 - Getting Started with Tensorflow

4th February
Completed Lessons 1 and 2 of Intro to Tensorflow for Deep Learning Course on Udacity and coded a simple Neural Network for a Linear Function using tensorflow.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day064.ipynb

Day 65 - Dense Networks vs CNN for Image Classification

5th February
Completed Lessons 3 and 4 of Intro to Tensorflow for Deep Learning Course on Udacity which are about using Dense Networks and CNN for Image Classification Task.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day065.ipynb

Day 66 - Horses or Humans Image Classification

6th February
Worked on training a CNN for classifying humans and horses using Tensorflow.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day066.ipynb

Day 67 - HackerEarth Airplane Accident Severity Challenge Part 4

7th February
Built a Deep Neural Network to classify severity of the Airplane Accident. Accuracy is around 94% on the dev set and got a 0.84 score on the competition test set which is not an improvement on the Gradient Boosting Model.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day067.ipynb

Day 68 - HackerEarth Airplane Accident Severity Challenge Part 5

8th February
Tried using an ensemble of Deep Neural Networks to classify severity of the Airplane Accident

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day068.ipynb

Day 69 - CNN for Coloured Images

9th February
Halfway through Lessons 5 of Intro to Tensorflow for Deep Learning Course on Udacity.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day069.ipynb

Day 70 - CNN for Coloured Images

10th February
Did 2nd half of Lessons 5 of Intro to Tensorflow for Deep Learning Course on Udacity.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day070.ipynb

Day 71 - Image Augmentation and Classification Exercise

11th February
Did Exercise of Lesson 5 of Intro to Tensorflow for Deep Learning Course on Udacity which is to classify flower images into 5 types.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day071.ipynb

Day 72 - Transfer Learning

12th February
Lessons 6 of Intro to Tensorflow for Deep Learning Course on Udacity.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day072.ipynb

Day 73 - Tensorflow - Saving and Loading Models

13th February
Lesson 7 and 9 of Intro to Tensorflow for Deep Learning Course on
Udacity.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day073.ipynb

Day 74 - Regular Expressions, Tokenization and Stemming

14th February
Started learning NLP from Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day074.ipynb

Day 75 - Minimum Edit Distance

15th February
Section 3 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day075.ipynb

Day 76 - Language Modeling and NGrams

16th February
Section 4 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day076.ipynb

Day 77 - Smoothing

17th February
Section 4 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day077.ipynb

Day 78 - Spelling Correction

18th February
Section 5 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day078.ipynb

Day 79 - Text Classification and Naive Bayes

19th February
Section 6 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day079.ipynb

Day 80 - Text Classification using NLTK

20th February
Watched videos from Sentdex's NLP with NLTK Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day080.ipynb

Day 81 - Text Classification using NLTK 2

21st February
Implemented Text Classification with help of Sentdex's NLP with NLTK Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day081.ipynb

Day 82 - Sentiment Analysis

22nd February
Section 7 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day082.ipynb

Day 83 - Discriminative Models

23rd February
Section 8 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day083.ipynb

Day 84 - Discriminative Models 2

24th February
Section 8 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day084.ipynb

Day 85 - Named Entity Recognition

25th February
Section 9 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day085.ipynb

Day 86 - Sequence Models

26th February
Section 9 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day086.ipynb

Day 87 - Relation Extraction

27th February
Section 10 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day087.ipynb

Day 88 - Relation Extraction 2

28th February
Section 10 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day088.ipynb

Day 89 - Maximum Entropy Model

29th February
Section 11 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day089.ipynb

Day 90 - Maximum Entropy Model 2

1st March
Section 11 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day090.ipynb

Day 91 - Maximum Entropy Model 2

2nd March
Section 12 of Dan Jurafsky's NLP Course on Youtube

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day091.ipynb

Day 92 - Parsing

3rd March
Section 13 of Dan Jurafsky's NLP Course on Youtube and updated this readme to include a summary and upcoming learning plans.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day092.ipynb

Day 93 - Grammar Transfer

4th March
Section 15 of Dan Jurafsky's NLP Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day093.ipynb

Day 94 - CKY

5th March
Section 15 of Dan Jurafsky's NLP Course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day094.ipynb

Day 95 - Tokenizing, Stopwords and Stemming

6th March
Watched lectures from sentdex's NLP with Python and NLTK course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day095.ipynb

Day 96 - Preprocessing, POS Tagging, Chunking

7th March
Implemented Preprocessing Methods like Tokenization, Stemming and Stopword Removal. Watched lectures from sentdex's NLP with Python and NLTK course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day096.ipynb

Day 97 - Named Entity Recognition, Lemmatization, NLTK Corpora

8th March
Watched lectures from sentdex's NLP with Python and NLTK course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day097.ipynb

Day 98- Wordnet

9th March
Watched lectures from sentdex's NLP with Python and NLTK course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day098.ipynb

Day 99- Chat vs Article Text Classifier

10th March
Built a text classifier (into chat and article) very similar to the one discussed in the article 'Naive Bayes Classifier for Text Classification' by Jaya Aiyappan (classifying sentences into questions and statements.)

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day099.ipynb

Day 100 - Saving Models, Scikit-Learn Incorporation

11th March
Watched lectures from sentdex's NLP with Python and NLTK course on Youtube.

More: https://github.com/hithesh111/Hith100/blob/master/100Days/day100.ipynb