Ementorhub

What you'll learn

Understand the principles and functioning of various deep learning architectures and algorithms.

Implement neural networks using TensorFlow and Keras for various tasks such as image classification and natural language processing.

Evaluate the performance of different neural network models and identify the factors influencing their accuracy and efficiency.

Design and develop comprehensive deep learning projects, integrating multiple techniques and tools to address complex AI challenges.

Skills you'll gain

NumPy

Supervised Learning

Pandas (Python Package)

Scikit Learn (Machine Learning Library)

Seaborn

Machine Learning

Machine Learning Methods

Deep Learning

Jupyter

Computer Vision

Data Visualization

Artificial Neural Networks

Specialization - 3 course series

The included projects are designed to solve authentic problems by applying deep learning techniques to real-world datasets. Learners will engage with practical applications such as analyzing natural images, diagnosing medical conditions using X-ray images, and implementing advanced recurrent neural network models for tasks like text generation and part-of-speech tagging. These projects ensure that learners not only understand theoretical concepts but also gain hands-on experience, enabling them to apply their deep learning skills effectively in real-life scenarios.

Foundations of Deep Learning and Neural Networks

Advanced CNNs, Transfer Learning, and Recurrent Networks