This lecture covers advanced concept of energy based models. The lecture is a part of the Advanced energy based models modules of the the Deep Learning Course at NYU's Center for Data Science. Prerequisites for this course include: Energy-Based Models I, Energy-Based Models II, Energy-Based Models III, and an Introduction to Data Science or a Graduate Level Machine Learning course.

This lesson gives an introduction to deep learning, with a perspective via inductive biases and emphasis on correctly matching deep learning to the right research questions.

As a part of NeuroHackademy 2021, Noah Benson gives an introduction to Pytorch, one of the two most common software packages for deep learning applications to the neurosciences.

Learn how to use TensorFlow 2.0 in this full tutorial for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence.

Throughout the 8 modules in this course you will learn about fundamental concepts and methods in ML & AI like core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning.

In this hands-on tutorial, Dr. Robert Guangyu Yang works through a number of coding exercises to see how RNNs can be easily used to study cognitive neuroscience questions, with a quick demonstration of how we can train and analyze RNNs on various cognitive neuroscience tasks. Familiarity of Python and basic knowledge of Pytorch are assumed.

This lecture provides an introduction to the application of genetic testing in neurodevelopmental disorders.

In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.

The Allen Mouse Brain Atlas is a genome-wide, high-resolution atlas of gene expression throughout the adult mouse brain. This tutorial describes the basic search and navigation features of the Allen Mouse Brain Atlas.

The Allen Developing Mouse Brain Atlas is a detailed atlas of gene expression across mouse brain development. This tutorial describes the basic search and navigation features of the Allen Developing Mouse Brain Atlas.

This tutorial demonstrates how to use the differential search feature of the Allen Mouse Brain Atlas to find gene markers for different regions of the brain, as well as to visualize this gene expression in three-dimensional space. Differential search is also available for the Allen Developing Mouse Brain Atlas and the Allen Human Brain Atlas.

This lesson provides an overview of GeneWeaver, a web application for the integrated cross-species analysis of functional genomics data to find convergent evidence from heterogeneous sources.

This lesson provides a demonstration of GeneWeaver, a system for the integration and analysis of heterogeneous functional genomics data.

This lecture outlines GeneNetwork.org, a group of linked data sets and tools used to study complex networks of genes, molecules, and higher order gene function and phenotypes.

This tutorial shows how to use the UCSC genome browser to find a list of genes in a given genomic region.

This tutorial shows how to find all the single nucleotide polymorphisms (SNPs) upstream from genes using the UCSC Genome Browser.

This tutorial demonstrates how to find all the single nucleotide polymorphisms (SNPs) in a gene using the UCSC Genome Browser.

The Saved Sessions feature of the Browser has been around for quite some time, but many of our users have not made full use of it. This feature offers a great way to keep track of your thinking on a particular topic.

The Track Collection Builder is a new tool in the UCSC Genome Browser that provides a way to create grouped collections of sub-tracks with native tracks, custom tracks, or hub tracks of continuous value graphing data types.

This tutorial demonstrates the visibility controls on the Genome Browser, showing the effect on BED tracks, wiggle tracks, and Conservation tracks. It also discusses supertracks and composite tracks.

This tutorial describes the isPCR tool and demonstrates how to use it for predicting the size and location of PCR products and visualizing the genomic location on the genome. The tool operates on DNA templates for all organisms, and on human and mouse DNA/RNA. It also demonstrates how to use the Browser to obtain DNA sequences from the genome.