nikhileshwar-avs Goto Github PK
Name: Nikhileshwar AVS
Type: User
Company: PayPal
Bio: I am working as a Data Engineer at PayPal. I have a skillset in Big data technologies like Spark, Scala, Hadoop, and GCP and in analytics with python, tableau
Name: Nikhileshwar AVS
Type: User
Company: PayPal
Bio: I am working as a Data Engineer at PayPal. I have a skillset in Big data technologies like Spark, Scala, Hadoop, and GCP and in analytics with python, tableau
500 AI Machine learning Deep learning Computer vision NLP Projects with code
Advanced Natural Language Processing with TensorFlow 2, published by Packt
Applied ML Algorithms On Amazon Fine Food Reviews.
A python library to scrape data from amazon.com
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Basic Shiny App demonstrating application of ANOVA to user given dataset.
Assignment-07-Clustering-Hierarchical-Airlines. Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data include information on their mileage history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers.
Assignment-07-K-Means-Clustering-Airlines. Perform clustering (K means clustering) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data include information on their mileage history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers.
Assignment-08-PCA-Data-Mining-Wine data. Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it has 3 clusters)
Assignment-11-Text-Mining-01-Elon-Musk, Perform sentimental analysis on the Elon-musk tweets (Exlon-musk.csv), Text Preprocessing: remove both the leading and the trailing characters, removes empty strings, because they are considered in Python as False, Joining the list into one string/text, Remove Twitter username handles from a given twitter text. (Removes @usernames), Again Joining the list into one string/text, Remove Punctuation, Remove https or url within text, Converting into Text Tokens, Tokenization, Remove Stopwords, Normalize the data, Stemming (Optional), Lemmatization, Feature Extraction, Using BoW CountVectorizer, CountVectorizer with N-grams (Bigrams & Trigrams), TF-IDF Vectorizer, Generate Word Cloud, Named Entity Recognition (NER), Emotion Mining - Sentiment Analysis.
NLP: Sentiment Analysis or Emotion Mining on Amazon Product Reviews - Part-1. Let’s learn the NLP techniques to perform Sentiment Analysis or Emotion Mining on extracted Product Reviews from Amazon. Part-1 covers Text preprocessing and Feature extraction, the next part covers Sentiment Analysis or Emotion Mining on text corpus. https://medium.com/@vaitybharati/nlp-sentiment-analysis-or-emotion-mining-on-amazon-product-reviews-part-1-428d43112027
Text-Mining-Amazon-Reviews-using-Scrapy. Ever wondered? Life would be easier if there could be ways to know how well your product performs and what do people feel about your product? The Solution -Text Mining Techniques. https://medium.com/@vaitybharati/text-mining-how-to-extract-amazon-reviews-using-scrapy-5bd709cb826c
Machine Learning University: Accelerated Natural Language Processing Class
This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.
Big Data Hadoop Pig Hive Python Scala Spark Cassandra Kafka demo projects
Analysis of Booking.com Data Jobs
⭕️ Building Recommendation Engines in Python
Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)
A multiple linear regression model for the prediction of car prices.
Web scraping task given by Ignis Tech Solutions as a selection for internship.
A Code-First Introduction to NLP course
About this Course This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course.
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai:
:mag_right: Data analysis with real world data sets using Python :mag:
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.