Snorkel AI

JUNE 15, 2023

As more consumers get interested in that, eventually others pick up on that product. What we do is monitor all trends that we think could potentially lead to this scenario. To give you a peek behind the scenes, we currently monitor over 400,000 different distinct trends. We do that on top of big sources of data.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Snorkel AI

JUNE 15, 2023

As more consumers get interested in that, eventually others pick up on that product. What we do is monitor all trends that we think could potentially lead to this scenario. To give you a peek behind the scenes, we currently monitor over 400,000 different distinct trends. We do that on top of big sources of data.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Chatbots Life

APRIL 19, 2024

These queries fall into a more complex category and necessitate a more personalized touch. The support agent picks up the conversation right where the chatbot left off, addressing Sarah’s concerns in a friendly and knowledgeable manner. This is where the power of human intervention comes into play.

Chatbots 52

Chatbots Natural Language Processing Automation Python 52

Unite.AI

JUNE 30, 2023

This tailored feedback in the moment allows agents to build a relationship with the customer based on that particular customer’s experience and their voice signals picked up by the AI model. Cogito uses a ‘fairness’ dataset comprised of a large body of audio data where the speakers self-report different demographic categories.

Emotion AI 296

Emotion AI Machine Learning Conversational AI Natural Language Processing 296

Pragnakalp

NOVEMBER 8, 2023

These queries fall into a more complex category and necessitate a more personalized touch. The support agent picks up the conversation right where the chatbot left off, addressing Sarah’s concerns in a friendly and knowledgeable manner. This is where the power of human intervention comes into play.

Chatbots 52

Chatbots Natural Language Processing Python Automation 52

The MLOps Blog

JANUARY 5, 2023

Social media monitoring is a thing for a while now. Social media monitoring, when it comes to fashion, is also a thing now. You need to pick instances for big indexes. In the case of a new category, you wouldn’t support it right away. Then we have one image that is associated with a new category.

Computer Vision 52

Computer Vision Machine Learning ML Explainability 52

AWS Machine Learning Blog

MAY 7, 2024

The trend continued with Jane from Australia, who on Nov 12th requested a shipment of ten high-definition monitors with total of $9000, emphasizing the need for environmentally friendly packaging. Following her, on Nov 7th, Bob from UK ordered a bulk set of twenty-five ergonomic keyboards for his office setup with total of $1000.

Prompt Engineer 94

Prompt Engineer Prompt Engineering Large Language Models LLM 94

Viso.ai

APRIL 29, 2024

It consists of over 14 million hand-annotated images with over 20,000 categories. In SGD, instead of performing calculations on the whole dataset, which is computationally expensive, SGD randomly picks a batch of images, calculates loss, and updates the weight parameters. SGD is a variant of Gradient Descent.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Machine Learning 52

Heartbeat

APRIL 18, 2023

Here are some of the reasons why HAR is important: Healthcare : HAR can be used to monitor and analyze human movements for physical therapy, rehabilitation, and medical diagnosis. Import the library [link] Dataset This article’s dataset includes 15 distinct categories of human activities. Human movement Gif Why is HAR important?

Convolutional Neural Networks 52

Convolutional Neural Networks Deep Learning Neural Network Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

I actually did not pick up Python until about a year before I made the transition to a data scientist role. Can I go back and pick up the other option?” Mikiko Bazeley: With most boot camps, it comes down to picking the right one, honestly. They started off as doing data integrations, and then became the ML monitoring team.

ML 52

ML Data Scientist Machine Learning Data Science 52

The MLOps Blog

MARCH 23, 2023

These algorithms can be broadly categorized into two categories: Weight pruning : In weight pruning, individual weights in the LLM are removed based on their magnitude or importance, using techniques such as magnitude-based pruning or structured pruning. MP is to improve the efficiency of LLM inference without sacrificing accuracy.

NLP 115

NLP LLM Large Language Models Natural Language Processing 115

DataRobot Blog

NOVEMBER 3, 2022

That doesn’t include the challenges of deploying multiple models, generating predictions, taking actions based on predictions, and monitoring models to make sure they’re still accurate enough to rely on as situations change. As we’ve described segmented modeling so far, users define their own segments, or groups of series, to model together.

Data Scientist 52

Data Scientist Black Box AI Explainability Automation 52

PyImageSearch

NOVEMBER 6, 2023

Finding Unique Mask Values ( Lines 59-62 ) For segmentation tasks, each pixel in a mask corresponds to a particular class or category. These unique values represent the different classes/categories in the segmentation masks. Visualization of model predictions to monitor progress.

Computer Vision 67

Computer Vision Neural Network Deep Learning Categorization 67

Mlearning.ai

SEPTEMBER 4, 2023

User-generated prompts can be highly variable and affect the model’s reliability and performance without proper curation, monitoring, and oversight. 10] This paradox illustrates an obstacle between stateless models you don’t own (and can’t train or tune) and stateful models you can’t control or monitor. 21] Hyung Won Chung, et al.

Generative AI 52

Generative AI Large Language Models AI AI 52

PyImageSearch

JANUARY 8, 2024

This computation is done with tf.GradientTape() since we want tf to monitor gradients ( Line 99 ). How can we tackle this simple problem and enhance our model so that it not only correctly predicts categories on original images but also on sketches and cartoons of cats and dogs? Next, we compute the gradient of the loss w.r.t.

Computer Vision 64

Computer Vision Neural Network Deep Learning Artificial Intelligence 64

PyImageSearch

OCTOBER 2, 2023

Autoencoder Validation: The validate function is instrumental in monitoring our autoencoder’s performance at the end of each training epoch. Furthermore, there’s a diverse representation across classes, ensuring distinct visual differences between categories, such as between sneakers and ankle boots. Download the code!

Computer Vision 120

Computer Vision Deep Learning Neural Network Auto-complete 120

AWS Machine Learning Blog

SEPTEMBER 6, 2023

I think there is nothing.nnn—n**Categories:**nn- [Conversation (32)](./conversation/32.md)n nSummary:nnn### Response:n #Person1# tells Jason Mrs. Thompson once ditheist and #Person1# guesses she wants them to run for class monitors. Person2#: Make sure that you pick up a flyer with the information about the home.n#Person1#:

Auto-complete 97

Auto-complete Machine Learning ML Python 97

AWS Machine Learning Blog

SEPTEMBER 12, 2023

To facilitate our ML lifecycle process, we decided to adopt SageMaker to build, deploy, serve, and monitor our models. To monitor the performance of our deployed model, we implement a feedback loop between CRM and the data scientists to keep track of prediction metrics from the model.

Data Scientist 95

Data Scientist Data Science NLP Machine Learning 95

Bugra Akyildiz

MARCH 2, 2024

Earlier especially in computer vision, generally the problem, given an image or video, it was to predict a piece of text(category of a class, understanding the audio into text, translation, etc), now with multi-modal capabilities, we are trying to generate modalities from text. Such a simple slide, but it was a really good one.

LLM 52

LLM AI AI Computer Vision 52

AWS Machine Learning Blog

OCTOBER 4, 2023

Timely and accurate classification of medical images allows for early detection of diseases that aides in effective treatment planning and monitoring. It includes a representative collection of all important diagnostic categories in the realm of pigmented lesions. Select Standard build to start building the model.

Computer Vision 85

Computer Vision ML Natural Language Processing Categorization 85

The MLOps Blog

JUNE 5, 2023

One category to think about is if we don’t need to train models anymore for some set of things, What activities are we taking part in? For example, there’s all of this MLOps tooling, and the thing that’s kind of at the far end is monitoring, right? What are we doing, and what tools do we need?

Large Language Models 52

Large Language Models Machine Learning Software Engineer ML 52

The MLOps Blog

DECEMBER 29, 2022

I’d be recommending digging into tools that allow you to visualize GPU usage, like monitoring software, basically, to actually see you are taking advantage of this expensive hardware you’re using. May be useful When training ML models, you can monitor your hardware consumption (GPUs, CPUs, memory) using neptune.ai.

ML 52

ML Auto-complete Machine Learning Python 52

AWS Machine Learning Blog

JANUARY 9, 2023

The scatter-gather pattern allows you to combine results from inferences run on three different models and pick the most probable classification model. Operational costs are the combined costs of operating, monitoring, and maintaining the ML infrastructure. It has built-in capabilities to ensure high availability and resiliency.

ML 74

ML Auto-complete Auto-classification Deep Learning 74