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Text-classification-and-clustering
It demonstrates the example of text classification and text clustering using K-NN and K-Means models based on tf-idf features.Predict-the-Happiness-HackerEarth-Challenge
It uses 2-layered fully connected/Dense Neural network model to predict whether the hotel reviews at TripAdvisor site are positive sentiment or negative sentiment. It is a python implementation utilizing Keras library for DNN. This problem statement came from a HackerEarth challenge: "Predict the Happiness" The accuracy score achieved was 88% when prediction file (sample_submisson.csv) is uploaded to their portal. The link for corpus/dataset download is given in blog-post.index
My_SiteTitanic-Sink-Analysis
The project is based on statistical analysis with R, which provides the survival prediction based on age,sex ratio,tickets,male,female,children etc.ChatBot
This ChatBot is based on Python with NLTK. Its a basic chatbot.Sentiment-Analysis-using-tf-idf---Polarity-dataset
It uses machine learning models to do sentiment polarity analysis on movie reviews. In other words, to classify opinions expressed in a text review (document) in order to determine whether the reviewer’s sentiment towards the movie is positive or negative.Object-recognition
In this blog-post, we will demonstrate how to achieve 90% accuracy in object recognition task on CIFAR-10 dataset with help of following concepts: 1. Deep Network Architecture 2. Data Augmentation 3. RegularizationMail-Spam-Filtering
Mail-Spam-Filtering It uses machine learning models to predict whether the email is spam or ligitimate. Best thing would be to follow my blog-post for implementation. The description about the steps to build a spam filter from scratch can be read from my blog: https://appliedmachinelearning.wordpress.com/2017/01/23/nlp-blog-post/ It is a python implementation using Naive Bayes Classifier and Support Vector Machines from Scikit-learn ML library. The results has been shown on two publicly open corpus. Ling-spam corpus Euron-spam corpus The link for corpus/dataset download is given in blog-post. Note : Directory path used for training and testing models in lingspam_filter.py and euron-spamfilter.py needs to be properly set accordingly.Love Open Source and this site? Check out how you can help us