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ai102files

Azure AI Associate Cert

alpaca-trade-api-python

Python client for Alpaca's trade API

augmentor

Image augmentation library in Python for machine learning.

autodeeplab

boston_housing

An exploratory data analysis is performed and a regression model is used to predict house values. The prediction performance is optimized after tuning the model hyper-parameters to minimize bias/variance errors.

boston_housing_2

An exploratory data analysis is performed and a regression model is used to predict house values. The prediction performance is optimized after tuning the model hyper-parameters to minimize bias/variance errors.

claim_approval

cloudml-samples

Samples for Google Cloud Machine Learning Engine

cognitive-services-python-sdk-samples

Learn how to use the Cognitive Services Python SDK with these samples

commondatamodel

Definition and DDLs for the OMOP Common Data Model (CDM)

customer_segments

The Principal Component Analysis (PCA) is implemented on a dataset (from 440 clients of a wholesale distributor with variables related to its clients' total spending values on different product categories) and the first principal components are used to cluster the clients into an optimal number of segments. Useful information is derived from segments that will help the wholesale distributor to assess changes to services via A/B testing on every segment.

dashboard

General-purpose web UI for Kubernetes clusters

deep-gauge

Deep gauge (using Tensorflow to read gauges)

deepgauge-ml-demo

deeplab_v3

Tensorflow Implementation of the Semantic Segmentation DeepLab_V3 CNN

docker-airflow

Docker Airflow - Contains a docker compose file for Airflow 2.0

docker-guides

Official guide repo used to accompany video tutorials in the docker course.

dog_app

Convolutional Neural Networks (CNN) are designed via transfer learning using bottleneck features from VGG-16 and ResNet-50 architectures. An accuracy of around 82% is achieved for the prediction of dog breeds (133 categories) from dog images.

dss

code for "Deeply supervised salient object detection with short connections" published in CVPR 2017

earthengine-api

Python and JavaScript bindings for calling the Earth Engine API.

effectivetensorflow

TensorFlow tutorials and best practices.

featureselectionga

Feature Selection using Genetic Algorithm (DEAP Framework)

finding_donors

Different classification algorithms are used to predict income levels of potential donors. The hyperparameters of the classifiers are optimized via grid_search and, among others, an ensemble classifier with the highest prediction performance is selected for this classification project.

food_data_bokeh

google-cloud-4-words

The Google Cloud Developer's Cheat Sheet

iceberg_ship

CNN architectures are designed to predict satellite images with an iceberg. An accuracy of around 87% is achieved in this binary classification project using a model with four convolution layers and one fully connected dense layer.

imdb_rating

The text data of 25000 labeled (positive and negative) IMDB reviews are processed and used to train a deep neural network model using Keras.

ingress-controller-v1.9.0

https://youtu.be/o6gxAsgWdBM

iotcore-heartrate

k8_python_client

Official Python client library for kubernetes