Online or onsite, instructor-led live TensorFlow training courses demonstrate through interactive discussion and hands-on practice how to use the TensorFlow system to facilitate research in machine learning, and to make it quick and easy to transition from research prototype to production system.
TensorFlow training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live TensorFlow training can be carried out locally on customer premises in Central or in NobleProg corporate training centers in Central.
Frasers Tower is a 38-storey Grade A office development with a three-storey cascading retail podium strategically located at the gateway to the dynamic Central Business District.
Only U Space
10 Anson Rd, #31-06 International Plaza , Singapore 079903, Singapore, 079903
International Plaza is a 50-storey office cum residential complex situated in Singapore’s CBD. The construction was part of a grand redevelopment plan for the central area of Singapore.
The closest MRT station is Downtown (DT17) on the Downtown Line. It is about a 2–3 minute walk from Asia Square Tower 1.
Take the Downtown Line to Downtown MRT (DT17).
Use Exit G (the building's official site lists Exit G).
Walk toward Asia Square Tower 1 / 8 Marina View.
Enter Tower 1 and take the lift to Level 42 or 43
Other convenient stations:
Shenton Way (TE19) — about 2–5 min walk.
Marina Bay (NS27/CE2/TE20) — about 4–6 min walk.
Raffles Place (NS26/EW14) — about 6 min walk.
By bus
There are several nearby bus stops. The closest are around Downtown MRT / Central Boulevard and are about a 4-minute walk away. Services include 97, 106, 133, 502 and 646 at Central Blvd – Downtown Stn Exit E.
Another nearby stop is One Raffles Quay, served by buses including 10, 57, 70, 75, 100, 107, 130, 131, 162, 167, 186 and 196.
This instructor-led, live training in Central (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.
By the end of this training, participants will be able to:
Build and train convolutional neural networks (CNNs) using TensorFlow.
Leverage Google Colab for scalable and efficient cloud-based model development.
Implement image preprocessing techniques for computer vision tasks.
Deploy computer vision models for real-world applications.
Use transfer learning to enhance the performance of CNN models.
Visualize and interpret the results of image classification models.
This instructor-led, live training in Central (online or onsite) is aimed at intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.
By the end of this training, participants will be able to:
Set up and navigate Google Colab for deep learning projects.
Understand the fundamentals of neural networks.
Implement deep learning models using TensorFlow.
Train and evaluate deep learning models.
Utilize advanced features of TensorFlow for deep learning.
This instructor-led, live training in Central (online or onsite) is aimed at data scientists who wish to use TensorFlow to analyze potential fraud data.
By the end of this training, participants will be able to:
Create a fraud detection model in Python and TensorFlow.
Build linear regressions and linear regression models to predict fraud.
Develop an end-to-end AI application for analyzing fraud data.
This instructor-led, live training in Central (online or onsite) is aimed at developers and data scientists who wish to use Tensorflow 2.x to build predictors, classifiers, generative models, neural networks and so on.
By the end of this training, participants will be able to:
Install and configure TensorFlow 2.x.
Understand the benefits of TensorFlow 2.x over previous versions.
Build deep learning models.
Implement an advanced image classifier.
Deploy a deep learning model to the cloud, mobile and IoT devices.
This 35-hour course in Central covers deep neural network fundamentals, including CNNs, RNNs, and generative models like GANs. Participants gain hands-on experience with Theano and TensorFlow, learning to build, train, and deploy production-grade deep learning models for real-world applications.
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Testimonials (1)
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
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