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Building a Logistic Regression Classifier in PyTorch

Machine Learning Mastery

Last Updated on December 30, 2022 Logistic regression is a type of regression that predicts the probability of an event. The formula of logistic regression is to apply a sigmoid function to the output […] The post Building a Logistic Regression Classifier in PyTorch appeared first on MachineLearningMastery.com.

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Meet the winners of the Mars Spectrometry 2: Gas Chromatography Challenge

DrivenData Labs

The goal of the Mars Spectrometry 2: Gas Chromatography Challenge was to build a model to automatically analyze gas chromatography–mass spectrometry (GCMS) data collected for Mars exploration. The Challenge Mass spectrometers are now, and will continue to be, a key instrument for missions searching for life and habitability on other planets.

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Consolidated Kaggle datasets for learning data science

Mlearning.ai

Split the dataset and apply simple machine learning models (like logistic regression or decision trees) to predict survival rates. Try out simple machine learning models (like Naive Bayes or logistic regression) to classify fake and real news. In this project: First, get the gist of the problem and the data.

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Meet the Final Winners of the U.S. PETs Prize Challenge

DrivenData Labs

Privacy-enhancing technologies (PETs) have the potential to unlock more trustworthy innovation in data analysis and machine learning. Federated learning is one such technology that enables organizations to analyze sensitive data while providing improved privacy protections. That’s why the U.S. The goal of the U.S.-U.K. This post introduces the U.S.

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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

Techniques like regression analysis, time series forecasting, and machine learning algorithms are used to predict customer behavior, sales trends, equipment failure, and more. Certainly, you need to ensure that while you target a specific job role in different companies, you have the skills and expertise as well.

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Classification in ML: Lessons Learned From Building and Deploying a Large-Scale Model

The MLOps Blog

A Multiclass Classification is a class of problems where a given data point is classified into one of the classes from a given list. To solve this problem of product search, one needs to build a classification solution where the number of classes is equal to the number of unique products, which could be in the order of millions.

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Building a Sentiment Classification System With BERT Embeddings: Lessons Learned

The MLOps Blog

There are usually three different ways of implementing a sentiment classification system: Rule-based approach: In this approach, a set of predefined rules are used to classify the sentiment of the text. If any of these words are detected in the text, then it is classified in one of the given sentiment categories.