Deep Learning Crash Course for Beginners with Python: Theory and Applications of Artificial Neural Networks, CNN, RNN, LSTM and Autoencoders using … Learning & Data Science for Beginners)

Price: $24.99 – $20.50
(as of Dec 17,2024 02:12:54 UTC – Details)

Welcome to our Deep Learning Crash Course for Beginners with Python! In this post, we will cover the theory and applications of artificial neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), long short-term memory (LSTM) networks, and autoencoders using TensorFlow, Keras, and other popular libraries.

Deep learning is a subset of machine learning that focuses on learning representations of data through multiple layers of neural networks. It has revolutionized many industries, from healthcare to finance to autonomous driving, and is a powerful tool for pattern recognition, natural language processing, computer vision, and many other tasks.

In this crash course, we will start by introducing the basics of neural networks and how they work. We will then dive into more advanced topics such as CNNs for image classification, RNNs for sequential data, LSTMs for time series analysis, and autoencoders for unsupervised learning.

Throughout the course, we will use Python as our programming language of choice, along with popular libraries like TensorFlow and Keras. We will also cover the basics of data preprocessing, model training, evaluation, and deployment.

Whether you are a complete beginner or have some experience with machine learning, this crash course will provide you with a solid foundation in deep learning and data science. Stay tuned for our upcoming posts, where we will dive deeper into specific topics and applications of deep learning. Happy learning!
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