Get Coupon Code What you'll learn How To Build Deep Neural Networks In Seconds Using Deep Learning Studio. How To Deploy Machine Learning Models Built Using Deep Learning Studio. How To Download Neural Network Models Built In Deep Learning Studio As Python / Keras / TensorFlow Script. We will develop Keras / TensorFlow Deep Learning Models using GUI and without knowing Python or programming. If you are a python programmer, in this course you will learn a much easier and faster way to develop and deploy Keras / TensorFlow machine learning models.
Get a solid understanding of Artificial Neural Networks (ANN) and Deep Learning Understand the business scenarios where Artificial Neural Networks (ANN) is applicable Building a Artificial Neural Networks (ANN) in R Use Artificial Neural Networks (ANN) to make predictions Use R programming language to manipulate data and make statistical computations Learn usage of Keras and Tensorflow libraries You're looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in R, right?You've found the right Neural Networks course!
This Neural Network tutorial will help you understand what is a neural network, how a neural network works, what can the neural network do, types of neural network and a usecase implementation on how to classify between photos of dogs and cats. Deep Learning uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Most deep learning methods involve artificial neural networks, modeling how our brains work. Neural networks are built on Machine Learning algorithms to create an advanced computation model that works much like the human brain.
At the end of the Course you will understand the basics of Artificial Neural Networks. The course will have step by step guidance for Artificial Neural network development in Python. I have 9 years of work experience as a Researcher, Senior Lecturer, Project Supervisor & Engineer. I have completed a MSc in Artificial Intelligence.
Get Coupon Code Hot & New What you'll learn Complete Understanding of Deep Learning from the Scratch Building the Artificial Neural Networks (ANNs) from the Scratch Artificial Neural Networks (ANNs) for Binary Data Classification Building Convolutional Neural Networks from the Scratch Convolutional Neural Network for Image Classification Convolutional Neural Network for Digit Recognition Breast Cancer Detection with Convolutional Neural Networks Convolutional Neural Networks for Predictive Analysis Convolutional Neural Networks for Fraud Detection Building the Recurrent Neural Networks (ANNs) from Scratch Review Classification with LSTM and GRU LSTM and GRU for Image Classification Prediction of Google Stock Price with RNN and LSTM Natural Language Processing Crash Course on Numpy (Data Analysis) Crash Course on Pandas (Data Analysis) Crash course on Matplotlib (Data Visualization) Description The Artificial Intelligence and Deep Learning are growing exponentially in today's world. There are multiple application of AI and Deep Learning like Self Driving Cars, Chat-bots, Image Recognition, Virtual Assistance, ALEXA, so on... With this course you will understand the complexities of Deep Learning in easy way, as well as you will have A Complete Understanding of Googles TensorFlow 2.0 Framework TensorFlow 2.0 Framework has amazing features that simplify the Model Development, Maintenance, Processes and Performance In TensorFlow 2.0 you can start the coding with Zero Installation, whether you're an expert or a beginner, in this course you will learn an end-to-end implementation of Deep Learning Algorithms List of the Projects that you will work on, Part 1: Artificial Neural Networks (ANNs) Project 1: Multiclass image classification with ANN Project 2: Binary Data Classification with ANN Part 2: Convolutional Neural Networks (CNNs) Project 3: Object Recognition in Images with CNN Project 4: Binary Image Classification with CNN Project 5: Digit Recognition with CNN Project 6: Breast Cancer Detection with CNN Project 7: Predicting the Bank Customer Satisfaction Project 8: Credit Card Fraud Detection with CNN Part 3: Recurrent Neural Networks (RNNs) Project 9: IMDB Review Classification with RNN - LSTM Project 10: Multiclass Image Classification with RNN - LSTM Project 11: Google Stock Price Prediction with RNN and LSTM Part 4: Transfer Learning Part 5: Natural Language Processing Basics of Natural Language Processing Project 12: Movie Review Classifivation with NLTK Part 6: Data Analysis and Data Visualization Crash Course on Numpy (Data Analysis) Crash Course on Pandas (Data Analysis) Crash course on Matplotlib (Data Visualization)