This course is from QTSInfo in which the in-depth concepts of Tensorflow and Keras will be taught to you. This is a course in which all the concepts of the Deep Learning framework will be covered. The Deep Learning with Keras and Tensorflow course has been developed by our expert trainers and they will teach you all the concepts with practical examples. The course will establish you as a deep learning researcher, data scientist, deep learning engineer, and many other types of Deep Learning Jobs.
This course in which our instructors will make you familiar with different fundamental concepts like an artificial neural network, PyTorch autoencoders, and many other concepts. We will also provide you with different projects and practical sessions so that you can understand all the concepts deeply. A Keras and Tensorflow tutorial will be available to you in which you will learn about different concepts of Tensorflow along with Keras.
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Who should take Keras vs Tensorflow
The course will be beneficial for the following people
People who want to develop data science applications through Keras and Tensorflow
People who want to learn Python concepts and use it in data science application development
People who want to use neural network in data science through Keras and Tensorflow
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Course curriculum / Syllabus
AI And Deep Learning Introduction
What is AI and Deep Learning?
Brief History of AI
Concept of UL, SL, and RL
Deep Learning: Successes Last Decade
Applications of Deep Learning
Challenges of Deep Learning
Deep Learning Project complete cycle
Artificial Neural Network
Perceptron Shallow Neural Network Vs Biological Neuron
Backpropagation
Role of Activation Functions and Backpropagation
Optimization
Regularization
Dropout layer
Neural Network and Tools
Applications of Deep Neural Network
Designing a Deep Neural Network
How to Choose Your Loss Function?
Tools for Deep Learning Models
Keras and its Elements
TFlearn Pytorch and its Elements
Deep Neural Net Optimization, Tuning, Interpretability
Optimization Algorithms
Momentum, SGD, Adagrad, NAG, RMSprop, Adadelta, Adam
Concept of Width vs Depth
Convolutional Neural Net
Success and History
CNN Network Design and Architecture
Deep Convolutional Models
Recurrent Neural Networks
Sequence Data
Sense of Time
RNN Introduction
LSTM (Retail Sales Dataset Kaggle)
Concept of GRUs (Gated Recurrent Units)
Comparison of LSTM and GRUs
Autoencoders
Introduction to Autoencoders
Applications of Autoencoders
Autoencoder for Anomaly Detection
Deep Learning with Keras and Tensorflow FAQ’s:
1.What is Keras?
Keras is a deep learning framework and professionals can perform different types of experiments. It works at a fast speed and it can help you to go ahead of your competitors.
2.What is Tensorflow?
Tensorflow is an open-source library which can be used easily in Python. The library consists of different functions which help in numerical calculation.
3.What is Tensorflow used for?
Tensorflow can be used for developing text based applications, image recognition, voice recognition, and other things