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500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

advanced-natural-language-processing-with-tensorflow-2

Advanced Natural Language Processing with TensorFlow 2, published by Packt

amazon-fine-food-review-using-all-algorithms

Applied ML Algorithms On Amazon Fine Food Reviews.

amazon-review-scraper

A python library to scrape data from amazon.com

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

anova-shinyapp

Basic Shiny App demonstrating application of ANOVA to user given dataset.

appreviewsnlp

assignment-07-clustering-hierarchical-airlines-

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-

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-

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

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.

assignment-11-text-mining-02-amazon-product-reviews

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

assignment-11-text-mining-amazon-reviews-using-scrapy

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

autoscrapper

aws-machine-learning-university-accelerated-nlp

Machine Learning University: Accelerated Natural Language Processing Class

azure-sdk-for-python

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-healthcare

bigdata

Big Data Hadoop Pig Hive Python Scala Spark Cassandra Kafka demo projects

booking.com

Analysis of Booking.com Data Jobs

bre

⭕️ Building Recommendation Engines in Python

bytewax-hopsworks-example

Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)

candidate-resume-recommendation-engine

car-price-prediction

A multiple linear regression model for the prediction of car prices.

coinmarketcap-scraping

Web scraping task given by Ignis Tech Solutions as a selection for internship.

course-nlp

A Code-First Introduction to NLP course

coursera--machine-learning-with-python-by-ibm

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.

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai:

credit-card-fraudlent

data-analytics-projects

:mag_right: Data analysis with real world data sets using Python :mag:

data-science-on-aws

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker