fields institute Optimization: Theory, Algorithms, Applications Lecture Series International Conference on Information Geometry for Data Science Institute for Data Science Foundations Blogs machine learning Lil'
and embedded hardware. Thanks to this, running deep neural networks and other complex machine learning algorithms is possible on low-power devices like microcontrollers. This course will give you a broad overview of how machine learning works, how to train neural networks, and how to deploy those...
Ant-algorithms. The ant colony optimisation is a set of algorithms inspired by ant behavior to solve a problem, find the best path between two locations. CLA. Cortical Learning Algorithm. For robotic learning, based on three properties, sparse distributed representation, temporal inference, on-lin...
trRosetta-based • AlphaFold2-based • DMPfold2-based • CM-Align • MSA transformer-based • DeepAb-based • TRFold2-based • GPT-based • ESM-based • Antiberta-based • Boltz-based • Sampling-algorithms 3) Function to Scaffold GAN-based • AutoEncoder-based •...
Understanding Deep Learning by Simon J.D. Prince Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz and Shai Ben-David Large Language Models A Visual Guide to Quantization: Demystifying the Compression of Large Language Models by Maarten Grootendorst Foundations of Larg...
8923 COMPARATIVE STUDY OF TOKENIZATION ALGORITHMS FOR END-TO-END OPEN VOCABULARY KEYWORD DETECTION 8418 COMPARING AND COMBINING AUDIO PROCESSING AND DEEP LEARNING FEATURES FOR CLASSIFICATION OF HEARTBEAT SOUNDS 7423 Comparing data-driven and handcrafted features for dimensional emotion recognition 7402 COMPARI...
HackerRank, a platform for learning algorithms and data structures and preparing for coding interviews, provides skills certifications tests in topics such as problem solving, Python, and JavaScript. Upon successfully clearing an assessment, you can promote yourself using the HackerRank certificate to peer...
Tequila is an Extensible Quantum Information and Learning Architecture where the main goal is to simplify and accelerate the implementation of new ideas for quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generali...
By the end of this module on Demonstrating Unsupervised & Reinforcement Machine Learning Algorithms with Python demos, learners will be able to: Model a k-means clustering algorithm through a demo; Develop an application demo employing DBSCAN clustering on a dataset; Demonstrate the use of COBOTs ...
spark In-memory cluster computing framework, up to 100 times faster for certain applications and is well suited for machine learning algorithms. hdfs Reliably stores very large files across machines in a large cluster. mapreduce-python IPython Notebook(s) demonstrating Hadoop MapReduce with mrjob fu...