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100-days-of-ml-code

100 Days of ML Coding

100-pandas-puzzles

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

100daysofmlcode

alexa_review_analysis

In this project , I have implemented Random Forest Classifier based Sentiment Analysis of Amazon's product Alexa reviews based on the reviews collected from around 10000 people.

alexa_sentiment

In this project I ahve developed a machine learning model to classify Amazon's product Alexa's Reviews collected from 10000 realtime customers of amazon to be positive or negative. Based on the customers reviews who have purchased the product, I have classified the reviews into positive or negative based on the sentiments showing in their reviews (Sentiment Analysis).

alexa_sentiment_analysis

In this project , I have implemented Random Forest Classifier based Sentiment Analysis of Amazon's product Alexa reviews based on the reviews collected from around 10000 people. Based on the customers reviews who have purchased the product, I have classified the reviews into positive or negative based on the sentiments showing in their reviews

apache-spark-tutorial

This is the repository for Apache Spark Projects from data handling to MLlib

applied_ds_python_univ_michigan

in this repo all the assignment works in the Applied Datascience with python course is there for reference

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

av-ltfs-data-science-finhack-ml-hackathon

L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’ organised by Analytics Vidhya

bang-housing

bang-webui

Bengaluru House Price Prediction

bangalore-housing

bank_fin_embedding

This repository consists of customized word embedding focused on banking and finance terms which will be helpful in analyzing and classifying financial sentiments or stock price sentiment analysis.

blockchain_development

boston_housing

In this project, we will evaluate the performance and predictive power of a model that has been trained and tested on data collected from homes in suburbs of Boston, Massachusetts.

charityml-finding-donors

CharityML is a fictitious charity organization located in the heart of Silicon Valley that was established to provide financial support for people eager to learn machine learning. After nearly 32,000 letters were sent to people in the community, CharityML determined that every donation they received came from someone that was making more than $50,000 annually. To expand their potential donor base, CharityML has decided to send letters to residents of California, but to only those most likely to donate to the charity. With nearly 15 million working Californians, CharityML has brought you on board to help build an algorithm to best identify potential donors and reduce overhead cost of sending mail. Your goal will be evaluate and optimize several different supervised learners to determine which algorithm will provide the highest donation yield while also reducing the total number of letters being sent.

corona-webapp

coursera

covid-19-webapp

customer_segments

A wholesale distributor recently tested a change to their delivery method for some customers, by moving from a morning delivery service five days a week to a cheaper evening delivery service three days a week.Initial testing did not discover any significant unsatisfactory results, so they implemented the cheaper option for all customers. Almost immediately, the distributor began getting complaints about the delivery service change and customers were canceling deliveries — losing the distributor more money than what was being saved. We will help the wholesale distributor to find what types of customers they have to help them make better, more informed business decisions in the future. Our task is to use unsupervised learning techniques to see if any similarities exist between customers, and how to best segment customers into distinct categories.

deep-learning-in-python

Hands-on, practical knowledge of how to use neural networks and deep learning with Keras 2.0

deep_learning

In this repo, all my deep learning projects are there

demo_chatbot_web

demo_rasa

demo_website

detecting-corona-using-modified-xceptionet

Detecting of COVID-19 induced Pneumonia in Chest X-ray Images using using Modified XceptionNet

detection_of_malicious_urls

In this project, we have detected the malicious URLs using lexical features and boosted machine learning algorithms

digit_recognizer_site

Handwritten Digit Recognition

dog_project