courseraАнализ данных

Deep Learning with TensorFlow: Build Neural Networks

Курс от EDUCBA

Уровень не указан≈ 6.3 чАнглийский

О курсе

Build a practical foundation in deep learning and learn to create neural network models with TensorFlow. This course guides you from perceptrons and core neural network principles to model initialization, multiclass classification, convolutional neural networks, and real-world image processing. Through step-by-step implementations, you will construct and train TensorFlow models, apply convolutional techniques, and develop image classification workflows using datasets such as dogs versus cats. You will also learn to use data generators, adapt pre-trained models, and fine-tune transfer learning strategies to improve accuracy on new datasets. Designed for learners who want to connect deep learning theory with practical application, the course explains not only how to implement each model but also the reasoning behind key development decisions. Its combination of conceptual clarity and hands-on TensorFlow practice will prepare you to design, train, and apply robust neural networks to specialized tasks. Enroll to strengthen your ability to build scalable deep learning solutions for AI projects and career development.

Навыки, которые вы освоите

Tensorflow Deep Learning Fine-tuning Transfer Learning Convolutional Neural Networks Image Analysis Computer Vision Network Architecture Data Preprocessing Classification Algorithms Design Data Processing Model Optimization Model Training Artificial Neural Networks

Программа курса

2 модулей · 24 учебных материалов

01Foundations of Deep Learning13 материалов

The Neural Network Blueprint

Overview of DLUTВидео Scenario of PerceptronВидео Creating Neural Network Using TensorFlowВидео Perform Multiclass ClassificationВидео

Учитесь у экспертов

EDUCBA

Преподаватель курса