Rakesh 's repositories
Topic-Modeling-Bidirectional-lstm--Implementation--NLP
In this Project the concept of Topic Modeling has been Implemented, basic NLP preprocessing has been performed and data has been prepared using tokenization and pad sequence techniques to model data with Bidirectional RNN lstm
Data-Science-Hackathon-And-Competition
Top 10 in MachineHack | Top 80 in AnalyticsVidya & Zindi | Hack AI
Automated-ML-Application-for-EDA-Streamlit-Deployment--Heroku
This project is designed as Automated Application for performing Exploratory Data Analysis for given Dataset to generate insights using Python, Streamlit. For executing all the operations customized function has been created and with support of these functions every step will be executed. EDA like basic information about data, Tabulation Analysis, Distribution Analysis, Correlation Analysis and it has been extended to perform Advance Statistical Analysis with some Basic Feature Engineering has been Automated. This Project has been Deployed with Streamlit in Heroku Cloud Platform
FIFA-World-Cup-Analysis
The Motive of this project is to analyze FIFA World Cup Data,we have the data from 1930 to 2014. The data we have is separated by Matches ,Players and Cup Holders since 1930 to 2014. Lot of Analysis has been done with nice Visualizations to understand and to get insights from data
Automated-ML-Application-for-Exploratory-Data-Analysis-Streamlit-Deployment
Complete EDA Will be automated and done by a single click like Aggregation Table, Cross Tabulation, Pearsonr Correlation, Spearman Correlation, Scatter plot, Distplot, Count plot, Histogram and some Plots using Plotly
Text-Summarizer-Flask-Deployment
This project is based on a Basic Text summarizer implemented with the concept of Cosine Similarity. Every basic preprocessing and Feature Engineering steps in Natural Language Processing is implemented and deployed as web API using Flask Deployment
IPL-Score-Prediction-with-Flask-Deployment-Heroku
This Project is based on Sports Analytics, it is implemented to predict the cricket score of the team and deployed as a web API using Flask. For Better results, I have not included the result as accurate score instead of that my prediction will be in a range of prediction -10and prediction +10
Movie-Recommendation-System-with-Sentiment-Analysis
Content based movie recommendation system with sentiment analysis
Text-Summarization-An-Extractive-Method-NLP
Utilizing NLTK package and techniques like Tokenization, Stemming, Lemmatization, Computing Similarity and Using Page-Rank Algorithm to summarize a 1-page paragraph in 10 sentences
Machine-Learning-Web-Apps
Building and Embedding Machine Learning Model into a Web App(With Flask,Streamlit,etc)
Diabetes-Prediction
This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage
Neural-Machine-Translation-NMT
Using Google Colab, we develop a NMT, language translator. Here, we do NMT to translate from English to Vietnamese.
Breast-Cancer-Prediction-1
Predicts whether the type of breast cancer is Malignant or Benign
NLP-Web-Apps
Natural Language Processing Web Apps
text-summarization
Automatic summarization is the process of shortening a text document with software, in order to create a summary with the major points of the original document. Technologies that can make a coherent summary take into account variables such as length, writing style and syntax.
summarizer
Text summarizer using Python NLP and Flask