Valerio Velardo - The Sound of AI Courses

How to Implement a Variational Autoencoder in Python and Keras

Implement a Variational Autoencoder using Python, TensorFlow, and Keras. Learn to modify the encoder, update loss functions, train the model, and visualize the latent space for data generation.

• YouTube
• 33 minutes
• On-Demand
• Free Video

How Is AI Revolutionising Music?

Explore how AI is transforming music creation, listening experiences, and soundtrack acquisition, revolutionizing the industry for listeners, musicians, and media creators alike.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Great AI Music Projects for Your Portfolio

Discover 7 impactful AI music projects to enhance your portfolio, showcasing skills in AI, audio processing, and coding to boost your chances of landing an AI music engineering job.

• YouTube
• 28 minutes
• On-Demand
• Free Video

From Autoencoders to Variational Autoencoders - Improving the Encoder

Explore the transformation from autoencoders to variational autoencoders, focusing on improved encoding using multivariate normal distributions for enhanced generative capabilities in AI and sound processing.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Generation with AutoEncoders - Results and Limitations

Explore image generation using autoencoders, analyze latent space representations, and understand limitations in generative tasks. Learn why variational autoencoders are necessary for improved generation.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Building and Training an Autoencoder in Keras - TensorFlow - Python

Learn to build and train autoencoders using Python, TensorFlow, and Keras. Explore encoder-decoder architectures, implement training with the MNIST dataset, and gain practical insights into autoencoder development.

• YouTube
• 27 minutes
• On-Demand
• Free Video

How to Implement Autoencoders in Python and Keras - The Decoder

Learn to implement the decoder component of autoencoders using Python, TensorFlow, and Keras. Covers building methods, layers, and architecture for generating sound with neural networks.

• YouTube
• 36 minutes
• On-Demand
• Free Video

How to Implement Autoencoders in Python and Keras - The Encoder

Learn to implement autoencoders in Python and Keras, focusing on building the encoder component. Covers autoencoder class construction, convolutional layers, bottleneck creation, and practical implementation.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Autoencoders Explained Easily

Intuitive explanation of autoencoders, covering key concepts like representation learning and latent space, with applications in data generation, denoising, and anomaly detection.

• YouTube
• 28 minutes
• On-Demand
• Free Video

How to Select a Research Topic for Your Paper

Learn effective strategies for selecting engaging AI audio research topics, from brainstorming concepts to developing research questions and approaches, ensuring your paper aligns with conference themes and personal interests.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Sound Generation with Deep Learning - Approaches and Challenges

Explore deep learning approaches for sound generation, including raw audio and spectrogram methods. Learn about challenges, architectures, and inputs used in creating AI-generated audio.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Covid-19 and Cough - This AI Predicts if You Have the Infection - Paper Explained

Análisis detallado de un sistema de IA que diagnostica COVID-19 mediante grabaciones de tos, explicando su funcionamiento, arquitectura y precisión.

• YouTube
• 48 minutes
• On-Demand
• Free Video

Announcing OpenSource Research - A Community-Driven Research Project

Participate in OpenSource Research, a collaborative AI music project aiming to advance the field through community-driven research and potential conference publication.

• YouTube
• 21 minutes
• On-Demand
• Free Video

How to Read AI Research Papers Like a Rockstar

Learn a 4-step strategy to effectively read and comprehend AI audio research papers, enhancing your skills as an AI engineer and fostering critical thinking in the field.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Mel-Frequency Cepstral Coefficients Explained Easily

Explore Mel-Frequency Cepstral Coefficients (MFCCs) in audio processing, covering their history, computation, visualization, and applications in speech and music analysis.

• YouTube
• 58 minutes
• On-Demand
• Free Video