sandeep-manikonda

AnomaliesDetection-with-TimeSeriesAnalysis

This is an experimental of anomalies detection by applying different approach to the problem. PCA component regularization method, K-Mean Clustering, SVM and Gausian Distribution models has been used to detect anomalies on time series data.

awesome-actions

A curated list of awesome actions to use on GitHub

awesome-courses

:books: List of awesome university courses for learning Computer Science!

bert

TensorFlow code and pre-trained models for BERT

bi-lstm-crf-tensorflow

Bidirectional LSTM + CRF (Conditional Random Fields) in Tensorflow

ChatterBot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

commitz

BUGZY - Automated machine learning model to predict if a git commit is a bug fix. Based on topic modeling and natural language processing, it is built with SVM and Latent Dirichlet Allocation (LDA).

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

Extractive-Text-Summarization

Extractive Text Summarization in Python

HackerrankPractice

170+ solutions to Hackerrank.com practice problems using Python 3, С++ and Oracle SQL

sandeep-manikonda/AnomaliesDetection-with-TimeSeriesAnalysis

This is an experimental of anomalies detection by applying different approach to the problem. PCA component regularization method, K-Mean Clustering, SVM and Gausian Distribution models has been used to detect anomalies on time series data.

sandeep-manikonda/awesome-actions

A curated list of awesome actions to use on GitHub

sandeep-manikonda/awesome-courses

:books: List of awesome university courses for learning Computer Science!

sandeep-manikonda/bert

TensorFlow code and pre-trained models for BERT

sandeep-manikonda/bi-lstm-crf-tensorflow

Bidirectional LSTM + CRF (Conditional Random Fields) in Tensorflow

sandeep-manikonda/ChatterBot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

sandeep-manikonda/commitz

BUGZY - Automated machine learning model to predict if a git commit is a bug fix. Based on topic modeling and natural language processing, it is built with SVM and Latent Dirichlet Allocation (LDA).

sandeep-manikonda/deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

sandeep-manikonda/Extractive-Text-Summarization

Extractive Text Summarization in Python

sandeep-manikonda/HackerrankPractice

170+ solutions to Hackerrank.com practice problems using Python 3, С++ and Oracle SQL

sandeep-manikonda/hello-world

First repo

sandeep-manikonda/IISLogAnalyzer

A Log Parser to analyze IIS Logfiles

sandeep-manikonda/ktext

Utilities for preprocessing text for deep learning with Keras

sandeep-manikonda/multivariate-lstm

sandeep-manikonda/nlp-recipes

Natural Language Processing Best Practices & Examples

sandeep-manikonda/NLP_for_ML

sandeep-manikonda/NLP_Projects

sandeep-manikonda/python-guide

Python best practices guidebook, written for humans.

sandeep-manikonda/Seq2Seq_Tutorial

Code For Medium Article "How To Create Data Products That Are Magical Using Sequence-to-Sequence Models"

sandeep-manikonda/topic_modeling_tutorial

Instructions & code for the EuroPython 2014 training session "Topic Modeling for Fun and Profit"

sandeep-manikonda/TopicModelling-LSA-LDA

Retrieving 'Topics' (concept) from corpus using (1) Latent Dirichlet Allocation (Genism) for modelling. Perplexity and Coherence score were used as evaluation models. (2) Latent Semantic Analysis using Term Frequency- Inverse Document Frequency and Truncated Singular Value Decomposition.

sandeep-manikonda/yake

Single-document unsupervised keyword extraction