chrispmaag
Machine learning software engineer. Passionate about building ML and computer vision applications that help solve real-world problems.
MetaSeattle, WA
Pinned Repositories
pulseaudio_speech_enhancement
Real-time speech enhancement for a better workflow. PyTorch deep learning model deployed as Flask application on GCP.
sneakers_pytorch_web_app
PyTorch classifier for sneakers
bubble_grader_computer_vision
Grade bubble sheet using computer vision
ssd_object_detection
Object detection using transfer learning on pre-trained object detector (SSD-ResNet50) for new class
flask_with_tensorflow_lite
Deploying TensorFlow Lite model using Flask
node_js_bootcamps
Backend for devcamper app using NodeJS, Express, and MongoDB
pix2pixGAN
Pix2Pix GAN for paired image-to-image translation to convert building facades to real buildings
circle_ci_hello_world
Learning CircleCI
circleci-demo-javascript-express
Sample Javascript/Express app building on CircleCI
clickstream_sequence_learning
Identify the better strategy for session level predictions that lead to personalization.
chrispmaag's Repositories
chrispmaag/machine-learning-engineering-for-production-public
Public repo for DeepLearning.AI MLEP Specialization
chrispmaag/node_js_bootcamps
Backend for devcamper app using NodeJS, Express, and MongoDB
chrispmaag/plotly_open_city_data_api
Connect to open city data through SODA API and visualize with Plotly
chrispmaag/circle_ci_hello_world
Learning CircleCI
chrispmaag/react-slingshot
React + Redux starter kit / boilerplate with Babel, hot reloading, testing, linting and a working example app built in
chrispmaag/circleci-demo-javascript-express
Sample Javascript/Express app building on CircleCI
chrispmaag/cloudformation_web_app
Deploy a high-availability web app using CloudFormation
chrispmaag/github-pages-with-jekyll
chrispmaag/pulseaudio_speech_enhancement
Real-time speech enhancement for a better workflow. PyTorch deep learning model deployed as Flask application on GCP.
chrispmaag/Flask-ML-Pipeline_GCP-Tutorial
chrispmaag/fastapi_model_deployment
Deploy machine learning model using FastAPI
chrispmaag/flask_with_tensorflow_lite
Deploying TensorFlow Lite model using Flask
chrispmaag/clickstream_sequence_learning
Identify the better strategy for session level predictions that lead to personalization.
chrispmaag/lstm_imdb_sentiment
Use LSTM to predict sentiment
chrispmaag/ssd_object_detection
Object detection using transfer learning on pre-trained object detector (SSD-ResNet50) for new class
chrispmaag/pix2pixGAN
Pix2Pix GAN for paired image-to-image translation to convert building facades to real buildings
chrispmaag/cycle_gan
Use CycleGAN to generate nighttime images from daytime images
chrispmaag/functional_programming
Functional programming community of practice template
chrispmaag/nlp_machine_translation
Translate English text into French using embeddings and bidirectional GRUs
chrispmaag/part_of_speech_tagging_with_hmm
Build Hidden Markov Model for part of speech tagging
chrispmaag/deploy_text_sentiment_sagemaker
Deploy PyTorch text sentiment model using Amazon SageMaker, Lambda, and API Gateway
chrispmaag/data_engineering
Data engineering projects with Spark, Airflow, Redshift, PostgreSQL and Cassandra
chrispmaag/recommendations_with_ibm
Recommendations using collaborative filtering and matrix factorization
chrispmaag/bubble_grader_computer_vision
Grade bubble sheet using computer vision
chrispmaag/sneakers_pytorch_web_app
PyTorch classifier for sneakers
chrispmaag/finding_lane_lines_p1_sdcnd
Detect lane lines for self-driving cars using OpenCV
chrispmaag/fastai_lesson1
Image classification of Google Image results using fastai v1 library
chrispmaag/disaster_response_ml_pipeline
Machine learning pipeline and web app for categorizing text data into multiple classes
chrispmaag/neural_network_in_numpy
Implement forward pass and backpropagation for neural network using Numpy
chrispmaag/PyTorch_Image_Classifier
Jupyter notebook and command line interface with optional arguments for classifying images with PyTorch