Pinned Repositories
amazon-sagemaker-from-idea-to-production-iris
amss
analytics-zoo
Analytics + AI Platform for Apache Spark and BigDL
automl
Google Brain AutoML
aws-cv-jumpstarter
Jump start your journey in Computer Vision on AWS
BayesCog_Wien
Teaching materials for BayesCog at Faculty of Psychology, University of Vienna
BayesianMMM
(ml) - python implementation of bayesian media mix modelling with shape and carryover effect
causalml
Uplift modeling and causal inference with machine learning algorithms
ecml-pkdd-2018
Scripts for ECML PKDD 2018 article: Similarity encoding for learning with dirty categorical variables
Nucleus-detection
Nuclei segmentation by Mask RCNN
aaryanMontana's Repositories
aaryanMontana/causalml
Uplift modeling and causal inference with machine learning algorithms
aaryanMontana/Nucleus-detection
Nuclei segmentation by Mask RCNN
aaryanMontana/amazon-sagemaker-from-idea-to-production-iris
aaryanMontana/automl
Google Brain AutoML
aaryanMontana/aws-cv-jumpstarter
Jump start your journey in Computer Vision on AWS
aaryanMontana/BayesCog_Wien
Teaching materials for BayesCog at Faculty of Psychology, University of Vienna
aaryanMontana/BayesianMMM
(ml) - python implementation of bayesian media mix modelling with shape and carryover effect
aaryanMontana/causal-book-code
aaryanMontana/cmdstanpy
CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan program and fit the model to data using CmdStan.
aaryanMontana/CNTK
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
aaryanMontana/colab-mask-rcnn
How to run Object Detection and Segmentation on a Video Fast for Free
aaryanMontana/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
aaryanMontana/Emotion
:smile: Recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.
aaryanMontana/ExperimentData
aaryanMontana/Face-and-Emotion-Recognition
Realtime person's face recognize and can classify emotion using webcam, video or images.
aaryanMontana/face_detection
face detection with multiple methods
aaryanMontana/face_recognition
A real time face recognition pipeline
aaryanMontana/facenet
Face recognition using Tensorflow
aaryanMontana/FaceSwap
Swap face between two photos.
aaryanMontana/gitdemo
aaryanMontana/ImageAI
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
aaryanMontana/ludwig
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
aaryanMontana/machine_learning_examples
A collection of machine learning examples and tutorials.
aaryanMontana/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
aaryanMontana/mmlspark
Microsoft Machine Learning for Apache Spark
aaryanMontana/NLP-Web-Apps
Natural Language Processing Web Apps
aaryanMontana/notes-on-causal-inference
Some notes on Causal Inference, with examples in python
aaryanMontana/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
aaryanMontana/probability
Probabilistic reasoning and statistical analysis in TensorFlow
aaryanMontana/resources
PyMC3 educational resources