If you're new to this technology, then don't worry - the course covers the topics from the basics. If you have done some programming before, you should pick it up quickly.

Go from beginner to mastery in Neural Networks with OpenCV's new course offering The "Deep Learning with Keras and TensorFlow" course is an intermediate level course, curated exclusively for both beginners and professionals. The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task. If you're new to this technology, then don't worry - the course covers the topics from the basics. If you have done some programming before, you should pick it up quickly.

The "Deep Learning with Keras and TensorFlow" course is an intermediate level course, curated exclusively for both beginners and professionals. The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task. If you're new to this technology, then don't worry - the course covers the topics from the basics. If you have done some programming before, you should pick it up quickly.

The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task. There are separate sections for Artificial Intelligence, Data Science with Python, Machine Learning, and Deep Learning with Keras and TensorFlow which lets you scale up these techniques. Don't worry if you've never used Python before; the course covers the topics from the basics. You should be able to pick it up fast if you have experience with programming.

The "Deep Learning with Keras and TensorFlow" course is an intermediate level course, curated exclusively for both beginners and professionals. The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task. If you're new to this technology, then don't worry - the course covers the topics from the basics. If you have done some programming before, you should pick it up quickly.

In December of 2021, we went over How to Build a Recurrent Neural Network from Scratch, How to Build a Neural Network from Scratch in Python 3, and How to Build a Neural Network with Sci-Kit Learn. As a continuation in the Neural Network series, this post is going to go over how to build a simple GRU model in Keras with Tensorflow. In this post we'll use Keras and Tensorflow to create a simple GRU model, and train and test it on the MNIST dataset. Here are the steps we'll go through: To follow along, you'll need to install tensorflow which you can do using the line in the terminal below. GRU stands for "Gated Recurrent Unit".

Earlier this month, we went over How to Build a Recurrent Neural Network from Scratch, How to Build a Neural Network from Scratch in Python 3, and How to Build a Neural Network with Sci-Kit Learn. As a continuation in the Neural Network series, this post is going to go over how to build a Recurrent Neural Network with Keras SimpleRNN in Tensorflow. In this post we'll use Keras and Tensorflow to create a simple RNN, and train and test it on the MNIST dataset. Here are the steps we'll go through: To follow along, you'll need to install tensorflow which you can do using the line in the terminal below. Using Keras and Tensorflow makes building neural networks much easier to build.

Getting started with deep learning has become very simple and convenient, all thanks to wonderful duo of keras and tensorflow. You just need to do some imports, define some layers and bingo, you have your deep learning architecture ready to be trained and eventually give some amazing results. Keras has made such an amazing abstraction that even a total stranger to the topic as well can start training their own deep learning models. However if you are calling yourself a Data Scientist/Machine Learning Engineer then having some basic understanding of what's happening under the hood is a must, I am not saying you need to exactly know the hundreds of lines of code behind it but at least have a some understanding what those lines of code are doing. Without wasting anytime lets dive into some of the most commonly used keras components and try to understand them piece by piece, this will involve a basic understanding of Object Oriented Programming but don't worry I will try to keep it as simple as possible.

Python was slowly becoming the de-facto language for Deep Learning models. In this course you will learn how to build powerful convolutional neural networks in R, from scratch. This special kind of deep networks is used to make accurate predictions in various fields of research, either academic or practical. If you want to use R for advanced tasks like image recognition, face detection or handwriting recognition, this course is the best place to start. All the procedures are explained live, step by step, in every detail. Most important, you will be able to apply immediately what you will learn, by simply replicating and adapting the code we will be using in the course.

Classifying emails (spam or not spam) with GloVe embedding vectors and RNN/LSTM units using Keras and TensorFlow in Python.