Neural Network Course with Python

This course of neuronal networks with Python addresses from the foundations to advanced applications of neural networks with Python. The key concepts of artificial neurons, training and optimization of models, using popular bookstores such as tensorflow and keras are explored. You will learn about deep networks (DNN), convolutionary (CNN) and recurring (RNN/LSTM), with a practical approach in the use of techniques such as regularization, activation and retropropication functions. In addition, the course introduces the adversarial generative Networks (GAN) and self -chirers, applying these models in real problems such as temporary image and series processing. You can master the field of artificial intelligence and neural networks.

- Understand the structure and functioning of artificial neurons and neuronal networks. - Apply retropropagation algorithms and optimization techniques in neuronal networks. - Implement neuronal networks in Python using libraries such as keras and tensorflow - Develop deep network models for data classification and regression. - Build convolutional networks and apply them in image processing. - Understand the use of recurring networks in temporal sequences and LSTM. - Explore the implementation of GAN and Self -Effed for data generation.

At the end of this course of neural networks with Python, you can work on the development of neural networks, Machine Learning engineering, data science or artificial intelligence specialist. You will have the ability to design and apply advanced solutions in sectors such as technology, health, financial analysis and image processing.

The neuronal networks with Python prepares you to design, implement and optimize neuronal networks in Python. It will provide you with the necessary skills to apply deep, convolutionary and recurring networks in complex problems of classification, prediction and data generation. In addition, it will allow you to address challenges in the field of artificial intelligence, working with bookstores such as Tensorflow and Keras.

The neuronal networks with Python is aimed at developers, data science, software engineering and students with interest in automatic learning. It is also suitable for artificial intelligence professionals who wish to specialize in neuronal networks and their practical application in Machine Learning projects.