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Deep Learning and Machine Learning with TensorFlow

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 Tensorflow.

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


SkillsFuture Credit Applicable for Individual

WDA Training Grant Applicable for Company

Course Code: CRS-N-0040561

Course Booking

$498.00

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.

Course Details

Day 1

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

Day 2


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

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Engineers

Prerequisite

Basic Python knowledge is assumed

Trainers

Machine Learning and Tensorflow TrainerJan 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.

Tensorflow TrainerSunny Prakash is a Big Data Architect with Programming Background . He has around 7 years of IT experience. He has worked on Various Enterprise level solution. He is skilled in Cloud computing and Big Data Solution building in various Industrial sector and domain.

With an Strong background in Coding skills, he has a strong grips on Java,Python ,Scala ,HTML,JavaScript, Node Programming. Data Science is another specification where he has worked with larger Enterprises for finding their Data Insight and building Machine Learning mode

Tensorflow TrainerDr. Yongxin (Steve) has more than five years of solid industrial and research experiences in data analytics. He held PdD on operations research in National University of Singapore. After his Phd study, he worked as data analyst and scientist in manufacturing and commodity trading companies. He is specialized in analyzing, visualizing and mining complex time series data using Python tools sucha as Pandas, Numpy, Matplotlib, SK-Learn, Tensorflow etc. He did research on predictive analytics on various systems e.g., Forex and commodity trading, system performance prediction, machine maintenance, etc. Besides data analytics using Python, he also extended his expertise in Microsoft Excel VBA, Hadoop big data platforms such as AWS and Microsoft Azure. In addition, he is strong in mathematical modelling and has cross-disciplinary domain knowledge in operations research, currency and commodity trading and industrial automation.

Tensorflow TrainerMichal Krason is an energetic researcher passionate about applications of data science. His focus is on the newest advancements in the field of machine learning, especially visual recognition, as well as deepening expertise in neuroscience to enhance his analyses with cross-domain insights. During 5 years in the industry he has been working on datasets from banking, medical, social sciences, logistics and other sectors, transforming raw data into actionable insights. His skills in R, Python and Matlab combined with academic background in mathematics and statistics enable deeper understanding of various models and frameworks used in the field.

Tensorflow TrainerMariusz Kozłowski is an energetic and optimistic individual who has a passion for business change, improvement, analysis with experience in distilling mountains of data into clear insights that can support business decisions. I have strong background in statistics and applied mathematics with big interest in data mining and machine learning methods in finance and biostatistics area. As an achiever and discoverer I took several months' career break to pursue love to travel. Being a globetrotter fueled my creativity and enhanced relationship with technology

Tensorflow TrainerMing Liang is an up-and-coming developer with expertise ranging from deep learning to hardware like the raspberry pi. He specialises mostly in the area of data science and machine learning and has won several hackathons and is ranked highly in international competitions. Furthermore, he has also done projects as part of the maker community in Singapore and build his own 3D printer as well

Customer Reviews (9)

Will RecommendReview by Lawrence Choo
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 7/24/2017)
Might RecommendReview by Cai Zhi Qiang
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 7/20/2017)
Will RecommendReview by Justin Ker
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Fantastic course! Trainer was very knowledgeable with the latest aspects of machine learning. Would definitely recommend this course. Five stars!

More time with TF learn / Keras and less time with Tensor flow (Posted on 7/18/2017)
Will RecommendReview by Esther Ng
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 7/18/2017)
Will RecommendReview by Foo Yee Ling
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Provide more guidance in installing the open source tools across various platforms (e.g., windows, linux, etc) (Posted on 7/17/2017)
Might RecommendReview by Samuel Wong
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 6/28/2017)
Great courseReview by Pier
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Learnt a lot from this course, great trainer.
I do think that 3 days would be just right as the coverage is a tad intense. (although I do understand why it is 2 days ;) ) (Posted on 5/22/2017)
Will RecommendReview by Saranya Kandan
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Add one more day to the course, to explain certain concepts in detail. Touching upon some theory would also be good - like back propagation (Posted on 5/22/2017)
Will RecommndReview by Peter Cronje
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
The course should possibly be 3 days as there is allow to cover and allot more that can be covered.


Please like our facebook page https://www.facebook.com/TertiaryCourses/ and enjoy 10% discount for our next course using the discount code "LIFELONGLEARNING" (Posted on 3/27/2017)

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