Convolutional Neural Networks in TensorFlow

Colleagues, join the 109k developers enrolled in the Convolutional Neural Networks in TensorFlow training program.  If you want to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization. Gain high demand skills in Inductive Transfer, Augmentation, Dropouts, Machine Learning and Tensorflow. Training modules include: 1) Exploring a Large Dataset - basic image classification, and you learned a little bit about Convolutional Neural Networks (ConvNets). In this course you'll go deeper into using ConvNets will real-world data, and learn about techniques that you can use to improve your ConvNet performance, particularly when doing image classification!In Week 1, this week, you'll get started by looking at a much larger dataset than you've been using thus far: The Cats and Dogs dataset which had been a Kaggle Challenge in image classification, 2) Augmentation: A technique to avoid overfitting - namely that your model is very good at classifying what it is trained for, but not so good at classifying things that it hasn't seen. In order to generalize your model more effectively, you will of course need a greater breadth of samples to train it on. That's not always possible, but a nice potential shortcut to this is Image Augmentation, where you tweak the training set to potentially increase the diversity of subjects it covers, 3) Transfer Learning - where people with models trained on large datasets train them, so that you can either use them directly, or, you can use the features that they have learned and apply them to your scenario, 4) Multiclass Classifications - when moving beyond binary into Categorical classification there are some coding considerations you need to take into account.

Enroll today (teams & execs welcome): https://tinyurl.com/yckpmbjh 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy