pranzell Goto Github PK

1.introduction_to_python

This repository contains simple Python programs to get started.

10.recommender_systems

This repository contains use of Classification techniques to make a compatible Netflix Movie Recommender System from scratch. It recommends missing values of "Ratings" by users who have rated atleast some movies.

11.perceptron

This repository contains the basics of a Perceptron. Using some example data-sets, it shows how a perceptron works. Each data-set contains two attributes (X1, X2) with a target variable (Y). The model predicts and tells which models are linearly separable and which are not.

12.neural_network_dnn

This repository dives into the basics of a Deep/Dense Neural Netowrk. It contains an example of building a DNN model from Scratch and also contains an example which uses a KERAS API call. The example contains Energy Efficiency Example which has 8 inputs and 2 output responses.

13.neural_network_cnn

This repository dives into the basics of a Convolutional Neural Networks. And also shows usage in some examples.

14.neural_network_rnn

This repository dives into the basics of a Recurrent Neural Netowrk. It contains an example of a RNN network using Keras API to predict: (i). A single character following a series of characters, (ii). A word following a series of words(sentence). Also it contains the usage of LSTM networks.

15.natrual_language_processing

This repository dives into the basics of a Natrual Language Processing. It contains different kind of tokenization, removal of stop words, lemmatizing, POS tagging, Custom POS Tagging using Brill Tagger, Chunking.

16.nlp_word2vec

This repository dives into the basics of a Word2Vec Module. It shows the usage of word2vec in converting words into vectors for processing in ML Models.

17.nlp_word_movers_distance

This repository dives into the basics of a Word Mover's Distance Module. It shows us how to use WMD Model to predict semantic similarity between two sentences.

18.nlp_doc2vec

This repository dives into the basics of a Doc2Vec Module. It shows us how to compute similarity between two documents.

19.nlp_tf_idf

This repository dives into the basics of a TF-IDF Module. It shows us how to compute similarity between two documents.

2.introduction_to_python_advanced

This repository contains few advanced assignments/examples in Python to get you started towards Data Science field. It also contains two PDF files detailing the mathematical theorems used in the examples.

20.nlp_bm_25

This repository dives into the basics of a BM-25 Module. It shows us how to compute similarity between two documents.

21.nlp_sentence_paragraph_similarity

This repository shows us how to compute similarity between a Sentence and few paragraphs. This also explains how to point to a particular paragraph in a document from where the question was asked.

22.nlp_sentence_document_similarity

This repository shows us how to compute similarity between a Sentence and many Documents. Document giving the best score on similarity index as according to different models (BM_25, TFIDF, Doc2Vec, WMD) will be the actual document from where the Sentence has been taken.

23.q-a_chatbot_ipl_draft

This is a Q&A ChatBot based on NLP statistics which responds to statistical based Questions on Indian Premier League Season 1 (2008). This model is based on supervised learning algorithms with limited approach to user questions.

24.q-a_chatbot_ipl_final

This is a Q&A ChatBot based on NLP statistics which responds to statistical based Questions on Indian Premier League Season 1 (2008). This model is based on supervised learning algorithms with limited approach to user questions.

25.q-a_chatbot_capstone

This is a Q&A Conversation Bot based on NLP tools which responds to user queries by pointing to a paragraph from a bunch of documents. This in turns an unsupervised learning problem into supervised learning using negative sampling.

3.python_for_data_science_numpy

This repository contains examples in Python to get you started towards Data Science field. It contains examples related to use of Python's 'NUMPY' package.

4.python_for_data_science_pandas

This repository contains few examples related to use of Python's 'PANDAS' package. Deals with day-to-day usage of Pandas in exploring Datasets.

5.python_for_data_science_pandas_examples

This repository contains examples related to use of Python's 'PANDAS' package at an expert level. Involves exploring, group-by, drawing plots, generating inferences, etc.

6.exploring_data_set

This repository contains use of Python to explore data-sets. It consists of various analysis, plotting, visualization (Heat Maps, Boxplots, etc) to draw inferences from a data given.

7.linear_regression

This repository contains use of Machine learning models to understand Regression. In this file, it explores the use of sci-kit learn to understand Linear Regression. It further explains Cross Validation technique to use K-Folds. It also explains Ridge and Lasso Regression techniques.

8.linear_regression_advanced

This repository contains use of Linear Regression model to solve some industry problems. Each example gives us a brief about the problem statement and the data-set involved.

9.classification

This repository contains use of Machine learning models to understand Classification techniques such as Logistic Regression, Comaprison between Linear & Logistic models, Decision Trees, Random Forest algorithms. It also contains the understanding of Label Encoding the data-set.

cybersecurity_datascience

Applying "ThePhish: an automated phishing email analysis tool" on parsed emails.

get_historical_tweets

Need access to Twitter data? Struggling with managing a developer account? This will help you get started and have access to almost 20 years of historical tweets.

invoice-meta-data-extraction-engine

This repo deals with open-sourced exploration for extracting meta-data from PDF files.

k_nearestneighbours

This tells about the KNN algorithm coded in Python from Scratch (Mathematical approach) and using sklearn libraries

ml-for-good-clincial-ai