Unite.AI

DECEMBER 1, 2023

looking for keywords or patterns in documents) to programmatically label millions of data points in minutes, rather than manually tagging one data point at a time. The Snorkel AI suite enables users to create labeling functions (e.g., Regardless of what kind of models a business needs, they will need high-quality labeled data to train it.

Data Scientist 147

Data Scientist Auto-classification AI AI 147

Towards AI

APRIL 12, 2024

Enhanced Partner Collaboration: Sharing real-time data in a supply chain will offer collaboration opportunities with various participants such as suppliers, distributors, and logistics service providers throughout the supply chain.

Machine Learning 67

Machine Learning Data Analysis Artificial Intelligence Artificial Intelligence 67

IBM Journey to AI blog

AUGUST 8, 2023

Whether you’re dealing with logistics, supply chains, audits, IT service management , maintenance operations, personnel management or even wellness programs, a comprehensive asset management solution can strengthen business functions, improve quality and efficiency and ultimately increase profits.

Automation 126

Automation Artificial Intelligence Artificial Intelligence AI 126

Artificial Corner

JULY 9, 2023

Image and text analysis: Unsupervised learning algorithms can automatically categorize and tag images, analyze text to discover topics or sentiments, and identify similarities within a large corpus of data. These are just a few examples of how unsupervised learning is making a significant impact across industries.

Algorithm 74

Algorithm Categorization Machine Learning Neural Network 74

Snorkel AI

MARCH 19, 2024

One of the first cases the Snorkel team worked on had 30% noisy ground truth, which is why the tags feature was added to the platform. For example, the model had to learn that questions about tracking cards and shipping issues should be tagged “Card Arrival.”

Data Scientist 52

Data Scientist AI AI LLM 52

Snorkel AI

MARCH 19, 2024

One of the first cases the Snorkel team worked on had 30% noisy ground truth, which is why the tags feature was added to the platform. For example, the model had to learn that questions about tracking cards and shipping issues should be tagged “Card Arrival.”

Data Scientist 52

Data Scientist AI AI LLM 52

Mlearning.ai

FEBRUARY 17, 2023

MLflow tracking steps Set where your run data is recorded (tracking URI) Create an experiment Start run Log parameters/metrics/artifacts, add tags Let’s see where your run data is recorded. Add tags to run. Several runs can be grouped into an “experiment” to easily manage the same task. Save evaluation metrics as a dictionary.

Machine Learning 52

Machine Learning Python Auto-complete Data Science 52

IBM Journey to AI blog

APRIL 18, 2024

While cost wasn’t the primary driver, it reflects a growing belief that the value generated by gen AI outweighs the price tag. This approach also serves to tailor solutions to specific use cases, avoid vendor lock-in and capitalize on rapid advancement in the field.

Neural Network 226

Neural Network LLM AI AI 226

AWS Machine Learning Blog

JANUARY 13, 2023

For Peering connection name tag , you can optionally name your VPC peering connection.Doing so creates a tag with a key of the name and a value that you specify. This tag is only visible to you; the owner of the peer VPC can create their own tags for the VPC peering connection. Choose Create peering connection.

Machine Learning 68

Machine Learning ML Categorization Deep Learning 68

Allen AI

AUGUST 18, 2023

In practice: We use fasttext’s language identification models to tag content by language. Our approach relies on a combination of logistic classifiers (content tagging) and regular expressions (PII detection). We use a fairly permissive threshold, keeping documents that have a likelihood over 50% of being in English.

Auto-complete 98

Auto-complete Large Language Models NLP Explainability 98

Pickl AI

APRIL 25, 2023

Apparently, Machine Learning has been able to solve complex business problems in the areas of finance, healthcare, manufacturing, and logistics. Using this technique, the network learns from data that gets a tag by changing the weights across the neurons. The process of backpropagation is important to train neural networks.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Natural Language Processing 52

Snorkel AI

FEBRUARY 13, 2024

The student model could be a simple model like logistic regression or a foundation model like BERT. In cases where the high-confidence subset of data appears sufficiently robust, data scientists could cast aside all records tagged as likely-incorrect and train their model with the remainder. How does LLM distillation work?

LLM 52

LLM Data Scientist Neural Network Data Science 52

Snorkel AI

FEBRUARY 13, 2024

The student model could be a simple model like logistic regression or a foundation model like BERT. In cases where the high-confidence subset of data appears sufficiently robust, data scientists could cast aside all records tagged as likely-incorrect and train their model with the remainder. How does LLM distillation work?

LLM 52

LLM Data Scientist Neural Network Data Science 52

AWS Machine Learning Blog

AUGUST 2, 2023

It allows users to quickly and easily find the images they need without having to manually tag or categorize them. We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. An example of a customized image search is Enterprise Resource Planning (ERP).

Automation 69

Automation Generative AI Metadata Data Scientist 69

NLP For Hackers

JULY 1, 2018

You can get the dataset from here: Kaggle IMDB Movie Reviews Dataset Let’s quickly explore the IMDB dataset: import re import pandas as pd def clean_review(text): # Strip HTML tags text = re.sub('<[^<]+?>', Logistic Regression is a classification algorithm that is really simple yet very useful and performant.

Deep Learning 52

Deep Learning Neural Network Algorithm Natural Language Processing 52

Viso.ai

FEBRUARY 7, 2024

Action recognition is typically applied in scenarios where understanding the overall action category is enough, such as video tagging, content-based video retrieval, and activity monitoring. This is done without providing temporal localization information.

Deep Learning 52

Deep Learning Computer Vision Robotics Convolutional Neural Networks 52

How to Learn Machine Learning

JANUARY 21, 2023

AI-enhanced decision making: AI will continue to be integrated into the decision-making processes of organizations, allowing them to make more accurate and efficient decisions in areas such as finance, manufacturing, and logistics. Tags: Artificial Intelligence trends, AI Trends, Artificial Intelligence, AI projects.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Robotics Natural Language Processing 52

The MLOps Blog

JANUARY 25, 2023

These embeddings are then used as inputs for any classification model like Logistic Regression, SVC, CNN, etc. For example, “I love being ignored” may be tagged as a negative example, and “I can be very ambitious” can be tagged as a positive example. This data is then used to train models and make inferences.

BERT 52

BERT Natural Language Processing ML Deep Learning 52

Marktechpost

JULY 17, 2023

Synthetic datasets are sometimes superior to real-world data since they are automatically tagged and can purposefully include uncommon but critical corner situations. Tonic data is used daily by thousands of developers in fields as diverse as healthcare, financial services, logistics, edtech, and e-commerce to build solutions more quickly.

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

John Snow Labs

JUNE 2, 2023

For example, a named entity recognizer annotator might identify and tag entities such as people, organizations, and locations in a text document, while a sentiment analysis annotator might classify the sentiment of the text as positive, negative, or neutral.

Deep Learning 98

Deep Learning NLP Convolutional Neural Networks Neural Network 98

Mlearning.ai

MAY 23, 2023

On the other hand, logistic and linear regression algorithms are the ones with a high bias. What is logistic regression? State an example where you have recently used logistic regression. Logistic Regression is also known as the logit model. We have Logistic Regression for that. What is a random forest?

Data Science 52

Data Science Neural Network Deep Learning Machine Learning 52

Probably Approximately a Scientific Blog

MARCH 8, 2016

I trained a simple logistic regression classifier, removing stop words and punctuation, and representing each document using CBOW with GloVe word embeddings (my personal favorite). We can also take the most common words in this cluster, automatically, and use them as "tags" that describe the topic. document_classification.py

Algorithm 52

Algorithm Natural Language Processing Machine Learning Python 52