Deep Learning and Machine Learning with TensorFlow

SkillsFuture Course - Deep Learning and Machine Learning with TensorFlow (Special Offer)

Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data. TensorFlow is one of the newest and most comprehensive libraries for implementing deep learning. This course will show you how to build deep learning applications using Tensor.

The topics include

• Installing TensorFlow
• Math Operations with TensorFlow
• Neural Networks with TensorFlow
• Deep Learning with Tensorflow
• Image Recognition with Convolutional Neural Network (CNN)
• Text Analysis with Recurrent Neural Network (RNN)
• Keras
• TFLearn

Module 1 Getting Started 

• What is TensorFlow
• Install and Run TensorFlow

Module 2 Basic Tensorflow Operations

• Constant
• Graph Operation
• Math
• Matrix
• Placeholder
• Variable

Module 3 Datasets

• Iris Flower Dataset
• MNIST Handwritten Digits Dataset
• CIFAR Image Dataset
• One Hot Encoding/Decoding
• Split Dataset to Training/Testing

Module 4 Machine Learning on TF

• TF Graph Model
• Loss Function 
• Optimizer
• Training
• Metrics

Module 5 Neural Network (NN)

• What is Neural Network 
• Activation Functions
• Create a Deep Neural Network on TF
• TensorFlow Playground

Module 6 Tensorboard

• What is Tensorboard?
• Visualize a Tensorboard Graph
• Output Data to Tensorboard

Module 7 Convolutional Neural Network (CNN)

• What is CNN?
• CNN Architecture
• Convolution
• Pooling and Stride
• Dropout

Module 8 Recurrent Neural Network (RNN)

• What is RNN?
• How to train a RNN
• Long Term Dependencies
• LSTM Cell
• GRU Cell

Module 9 Keras

• What is Keras?
• Install Keras
• Neutral Network with Keras
• Inception V3 Transfer Learning

Module 10 TFLearn

• What is TFLearn?
• Install TFLearn
• Neutral Network with TFLearn

SkillsFuture Credit Applicable for Individual

WDA Training Grant Applicable for Company
Course Code: CRS-N-0040561

For more details, please visit our website at 

https://www.tertiarycourses.com.sg/deep-learning-neural-network-tensorflow.html or contact us at [email protected]

Jan Idziak has 5 years of industrial and academic experience in Data Science, Deep Learning, and Data Visualizations. This year, he was invited to the Country of Australia to conduct and moderate Statistical Data Analysis with the Mathematics in Industry Study Group (MISG) in association with University of South Australia.Working across wide range of projects and sectors, he has designed various statistical models and machine learning tools, including portfolio pricing engines, customer segmentation systems, or product recommenders. When he worked in Business Intelligence department in Banking sector, as well as for United Nations, he was transforming raw data into meaningful and actionable insights. During his time as a president of the Financial Engineering Association, he organized few conferences and provided support and training for other members of the association. He has been providing coaching on topics such as scoring models, predictive modelling, personalized recommendation systems, deep learning, data visualization, or natural language processing;

Jan specializes in data analysis, visualization, and R package development. His main technical skill set consists of languages/tools like Python, SPSS, Statistica, Matlab, R, JS, D3, html, R (including shiny, Rmarkdown, and package development). In addiction, he has strong knowledge on most of the data mining algorithms, modern visualization and summarizing techniques.

Key in Promo Code "ILOVELEARNING" to enjoy 10% discount from total course fee.