Pinned Repositories
awesome-causality-algorithms
An index of algorithms for learning causality with data
fraud-detection-using-machine-learning
Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
Genetic-Algorithm-RNN
Using Genetic Algorithms to optimize Recurrent Neural Network's Configuration
incubator-pinot
Apache Pinot (Incubating) - A realtime distributed OLAP datastore
kaggle-toxic-comments
Ensemble stacking using Keras / Tensorflow. Used LSTM RNN, Logistic Regression & XGB Classifier for first level, and simple CNN for metalearning.
Legal-Text-Analytics
A list of selected resources, methods, and tools dedicated to Legal Text Analytics.
MIT-Data-Science
Spark-with-Python---My-learning-notes-
ETL pipeline using pyspark (Spark - Python)
Talk-to-R-Shiny
Voice Enabled Statistics with R
telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
abhishekms1047's Repositories
abhishekms1047/fraud-detection-using-machine-learning
Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
abhishekms1047/Legal-Text-Analytics
A list of selected resources, methods, and tools dedicated to Legal Text Analytics.
abhishekms1047/workshop
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
abhishekms1047/abhishekms.github.io
abhishekms1047/amazon-sagemaker-feature-store-end-to-end-workshop
abhishekms1047/avatarify-python
Avatars for Zoom, Skype and other video-conferencing apps.
abhishekms1047/awesome-software-analytics
Curated list of awesome resources and links about Software Analytics
abhishekms1047/aws-media-insights-engine
A serverless framework to accelerate the development of applications that discover next-generation insights in your video, audio, text, and image resources by utilizing AWS Machine Learning and Media services.
abhishekms1047/aws-mlops-framework
The AWS MLOps Framework solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.
abhishekms1047/BayesPy
Bayesian Inference Tools in Python
abhishekms1047/BERT_FeatureStore
Saving raw text embeddings intothe SageMaker Feature Store
abhishekms1047/cartoonify
Deploy and scale serverless machine learning app - in 4 steps.
abhishekms1047/chitra
chitra (चित्र) is a Deep Learning library for Model Building, Interpretability, Visualization, API Building & Deployment.
abhishekms1047/Cloudformation-Github-Actions-Demo
abhishekms1047/discovering-hot-topics-using-machine-learning
The Discovering Hot Topics Using Machine Learning solution helps brand-conscious customers understand the most popular topics being actively discussed by ingesting digital assets and performing near real-time inferences and analytics
abhishekms1047/improving-forecast-accuracy-with-machine-learning
The Improving Forecast Accuracy with Machine Learning solution generates, tests, compares, and iterates on Amazon Forecast forecasts. The solution automatically produces forecasts and generates visualization dashboards for Amazon QuickSight or Amazon SageMaker Jupyter Notebooks—providing a quick, easy, drag-and-drop interface that displays time series input and forecasted output.
abhishekms1047/langchain
⚡ Building applications with LLMs through composability ⚡
abhishekms1047/langchain-aws-template
Application template for service api using langchain and generative model services
abhishekms1047/mlops-amazon-sagemaker-devops-with-ml
Workshop content for applying DevOps practices to Machine Learning workloads using Amazon SageMaker
abhishekms1047/neo-ai-dlr
Neo-AI-DLR is a common runtime for machine learning models compiled by AWS SageMaker Neo, TVM, or TreeLite.
abhishekms1047/pennylane
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
abhishekms1047/predictive-maintenance-using-machine-learning
Set up end-to-end demo architecture for predictive maintenance issues with Machine Learning using Amazon SageMaker
abhishekms1047/rag-fusion
abhishekms1047/sagify
MLOps for AWS SageMaker. www.sagifyml.com
abhishekms1047/self-improving-ai
abhishekms1047/streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io
abhishekms1047/system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
abhishekms1047/test
this is to show my wife how to create repo
abhishekms1047/TikTokAnalytics
abhishekms1047/TinyLlama
The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.