Ementorhub

What you'll learn

Identify the key components of deep neural networks, and train real-world datasets using different RNN architectures

Design and implement text classification tasks using RNNs and TensorFlow

Differentiate between RNNs, LSTM, and GRUs through hands-on exercises

Skills you'll gain

PyTorch (Machine Learning Library)

Data Processing

Machine Learning Algorithms

Machine Learning

Deep Learning

Artificial Neural Networks

Python Programming

Data Analysis

Predictive Modeling

Tensorflow

Natural Language Processing

Network Architecture

Specialization - 3 course series

Learners will work on projects like creating an automatic book writer and a stock price prediction application, applying their RNN, LSTM, and TensorFlow skills to solve real-world problems and build practical, impactful solutions. Through these projects, they will gain hands-on experience in data preparation, model training, and evaluation, equipping them with the confidence to implement RNNs in diverse applications.

RNN Architecture and Sentiment Classification

Advanced RNN Concepts and Projects