An Overview on Multilayer Perceptron (MLP) [Updated]
A multilayer perceptron (MLP) is a field of artificial neural network (ANN). Learn ✓ single-layer ANN ✓ forward propagation in MLP and much more. Read on!
Multi-Layer Perceptron Learning in Tensorflow - GeeksforGeeks
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
Crash Course on Multi-Layer Perceptron Neural Networks - MachineLearningMastery.com
Artificial neural networks are a fascinating area of study, although they can be intimidating when just getting started. There is a lot of specialized terminology used when describing the data structures and algorithms used in the field. In this post, you will get a crash course in the terminology and processes used in the field of multi-layer […]
Logistic Regression is one of the basic and popular algorithms to solve a classification problem. It is named ‘Logistic Regression’ because its underlying technique is quite the same as Linear…
Logistic regression is a supervised learning algorithm used to predict a dependent categorical target variable. Learn more about logistic regressions and its applications.
Logistic regression: Definition, Use Cases, Implementation
Logistic regression is a popular classification algorithm, and the foundation for many advanced machine learning algorithms, Let's go through logistic regression basics, its real-life applications, and learn how to implement it.
Inspired by progress in large-scale language modeling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment generalist policy. The same network with the same weights can play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button presses, or other tokens. In this report we describe the model and the data, and document the current capabilities of Gato.
Megatron-Turing Natural Language Generation Megatron-Turing Natural Language Generation model (MT-NLG), is the largest and the most powerful monolithic transformer English language model with 530 billion parameters. This 105-layer, transformer-based MT-NLG improves upon the prior state-of-the-art models in zero-, one-, and few-shot settings. It demonstrates unmatched accuracy in a broad set of natural language tasks such as, Completion prediction, Reading comprehension, Commonsense reasoning, Natural language inferences, Word sense disambiguation, etc.
We’ve created an improved version of OpenAI Codex, our AI system that translates natural language to code, and we are releasing it through our API in private beta starting today. Codex is the model that powers GitHub Copilot, which we built and launched in partnership with GitHub a month
Announcing AI21 Studio and Jurassic-1 language models
AI21 Labs’ new developer platform offers instant access to our 178B-parameter language model, to help you build sophisticated text-based AI applications at scale
A GPT-3 rival by Deepmind Researchers at DeepMind have proposed a new predicted compute-optimal model called Chinchilla that uses the same compute budge...
Language modelling at scale: Gopher, ethical considerations, and retrieval
Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memories, and build mutual understanding. These are foundational parts of social intelligence. It’s why our teams at DeepMind study aspects of language processing and communication, both in artificial agents and in humans.