The Hsinchu Wishun centre

新竹暐順商務中心, 復興三路二段168號6F, 30273, 新竹, taiwan, 30274

T新竹暐順商務中心位於新竹高鐵竹北特區之商業區。從經貿大樓步行空橋只需1分鐘即可抵達的高鐵新竹站,同時緊連台鐵內灣支線六家站。 交通上極佔地利之便,通過1號國道和省道即能輕鬆抵達新竹科學工業園區(8公里)和新竹市中心(15公里)。 該中心是新竹地區少有的A級建築之一。新建成的複合式商業大樓涵蓋了購物商場、景觀餐廳、企業辦公和商務飯店等多元商業機能設施。鄰近之公園綠地和商務飯店包括水圳森林公園和新竹喜來登酒店。高科技企業環繞和頂級居住社區林立,正是希冀新創和擴展新竹地區業務之企業爭相進駐的新樞紐所在。雷格斯新竹暐順中心提供符合各類型及尺寸需求的彈性辦公空間服務方案,並以合理的價格提供全方位的優質服務。雷格斯新竹暐順中心位於新竹高鐵竹北特區商業樞紐,鄰近多元商業機能設施

子目錄 (10)

探索我們的課程

Introduction to Pre-trained Models

14 時間:

Advanced Machine Learning Models with Google Colab

21 時間:

Creating Custom Chatbots with Google AutoML

14 時間:

Optimizing AI Models for Edge Devices

14 時間:

Building AI Solutions on the Edge

14 時間:

Edge AI with TensorFlow Lite

14 時間:

AI-Powered Autonomous Systems

21 時間:

AI-Enhanced Yield Management in Semiconductor Production

14 時間:

Advanced AI Techniques for Semiconductor Design Automation

21 時間:

AI-Driven Process Optimization in Chip Fabrication

14 時間:

Apache Airflow for Data Science: Automating Machine Learning Pipelines

21 時間:

Advanced Stable Diffusion: Deep Learning for Text-to-Image Generation

21 時間:

AI-Powered Cybersecurity: Advanced Threat Detection & Response

28 時間:

Machine Learning with Google Colab

14 時間:

AI-Powered Cybersecurity: Threat Detection & Response

21 時間:

AlphaFold

7 時間:

Data Mining with Weka

14 時間:

Advanced Analytics with RapidMiner

14 時間:

Introduction to Stable Diffusion for Text-to-Image Generation

21 時間:

Machine Learning Fundamentals with Python

14 時間:

Machine Learning with Python

28 時間:

AdaBoost Python for Machine Learning

14 時間:

AutoML with Auto-Keras

14 時間:

AutoML

14 時間:

Machine Learning

21 時間:

Pattern Recognition

21 時間:

DataRobot

7 時間:

Feature Engineering for Machine Learning

14 時間:

Fundamentals of Artificial Intelligence (AI) and Machine Learning

28 時間:

Google Cloud AutoML

7 時間:

Machine Learning Algorithms in Julia

21 時間:

Kubeflow

35 時間:

Kubeflow Fundamentals

28 時間:

Kubeflow on AWS

28 時間:

Kubeflow on Azure

28 時間:

Mathematica for Machine Learning

14 時間:

Machine Learning for Banking (with Python)

21 時間:

Machine Learning and Big Data

7 時間:

Machine Learning Concepts for Entrepreneurs and Managers

21 時間:

Machine Learning for Finance (with Python)

21 時間:

MLflow

21 時間:

Machine Learning Fundamentals with Scala and Apache Spark

14 時間:

Introduction to Machine Learning

7 時間:

Machine Learning on iOS

14 時間:

Machine Learning for Mobile Apps using Google’s ML Kit

14 時間:

Machine Learning in business – AI/Robotics

14 時間:

Machine Learning for Robotics

21 時間:

Pattern Matching

14 時間:

Machine Learning with Random Forest

14 時間:

RapidMiner for Machine Learning and Predictive Analytics

14 時間:

Tensorflow Lite for Microcontrollers

21 時間:

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