Machine learning deep learning

Author(s): Omar U. Florez, Ph.D. A neural network is a clever arrangement of linear and non-linear modules. When we choose and connect them wisely, we have ...

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Transformer architecture models, particularly BERT, has demonstrated to be quite effective in many NLP tasks by just fine tuning a model…

Machine learning and deep learning are both branches of artificial intelligence that focus on enabling computers to learn from data and make predictions or decisions. Machine learning involves using algorithms to identify patterns in data and make predictions based on those patterns. deep learning is a subset of machine learning that specifically deals with neural networks, which are designed to mimic the human brain's structure. D transform data #Machinelearning #Deeplearning

A Brief Introduction to ChatGPT. ChatGPT is a language model released by… | by Ben | Generative AI

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Learn the difference between Deep Learning and Machine Learning in a subtle yet informative way. #deeplearning #machinelearning #ml #Ai

Which activation function do you use often in neural networks? 👇 Here's the list 📚 𝗦𝗶𝗴𝗺𝗼𝗶𝗱 - The sigmoid function squashes its input into the range… | 23 comments on LinkedIn

One common problem of machine learning is the "curse of high dimensionality". When there are too many attributes in the input data, many of the ML algorithms will be very inefficient or some of them will even be non-performing (e.g. in nearest neighbor computation, data points in a high-dimensional space are pretty much equal distance with each other). It is quite possible that the attributes we selected are inter-dependent on each other. If so, we may be able to extract a smaller subset of...

Long short-term memory (LSTM) units are units of a recurrent neural network (RNN). A common LSTM unit is composed of a cell, an input gate, an output gate and a forget gate. The cell remembers values over arbitrary time intervals and the three gates regulate the flow of information into and out of the cell. LSTM networks are well-suited to classifying, processing and making predictions based on time series data.

A Dive into Activation Functions in Neural Networks Neural Networks and Deep Learning https://www.clcoding.com/2023/12/neural-networks-and-deep-learning.html Supervised Machine Learning: Regression and Classification https://www.clcoding.com/2023/12/supervised-machine-learning-regression.html Mathematics for Machine Learning Specialization https://www.clcoding.com/2023/11/mathematics-for-machine-learning.html

Design Principles 7: Fail Safe Is Better Than Fool Proof This is one of Sociomedia’s 100 design principl...

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