This Week in Hadoop and More: Deep and Machine Learning Tools, Tips, and Projects

There's a lot going on in the world of Big Data, Deep Learning, and Machine Learning this week. Personally, I am working with Vamsi on some awesome content for an upcoming DZone item.   I'm also preparing for Oracle Code New York, where I will be doing a talk on NiFi, Deep Learning, Machine Learning, NLTK, streaming, IoT, and Java microservices. Not sure how I will cram that into 45 minutes at 5 p.m. with a hands-on demonstration — I think I will need compression. If you are at that event in two weeks, come say hi! Mention the secret password, "DZone," and get a free sticker.

This Week's Must-Downloads

• Visualizing your Deep Learning in TensorBoard for PyTorch and others with Python interfaces (GitHub).

• Running Keras in Production With Deep Learning 4J (GitHub): Deep Learning, JVM, Python, and containers. Check out the source for yourself in Using Python With Keras Intro of Deep Learning 4J (on top of Hortonworks HDP).

• HiveQLUnit for Unit Testing.

• Apache NiFi Custom Processor for Financial FIX .

Model Zoos — Gotta Grab 'Em All!

• Deep Learning 4J Model Zoo: They save lots of time — grab all the zoos you can. I wish there was a universal one.

• MXNet Model Zoo.

• Paddle Paddle Model Zoo.

• TensorFlow Models: I have used Inception and Syntaxnet from here.

• Caffe Model Zoo (GitHub).

• Tensorflow and Pytorch Models.

• Keras Model Zoo.

• Neon Model Zoo.

• Torch7 Model Zoo.

• Pytorch Vision: Models, Data Loaders, and More: This is cool.

• TensorFlow Models for PyTorch.

This Week's Must-Read

• Bringing FaceNet to Java.

• Face Recognition in Python: A must-have for Terminator robot projects.

• TensorFlow Primer.

• Data Parallel GPUs in Spark.

• COCO image recognition from Microsoft (GitHub).

• TensorFlow and on Hadoop.

• OpenCV Tutorial.

• Motion Detection With OpenCV.

I am hoping by the end of the month to detail my progress on my self-driving Raspberry Pi car, Raspberry Pi Deep Learning, Spark, Hadoop Cluster, and wrap-up from the Code NYC talk.