Snorkel AI

JULY 14, 2023

classification, information extraction) using programmatic labeling, fine-tuning, and distillation. Latest features and platform improvements for Snorkel Flow Snorkel Flow provides an end-to-end machine learning solution designed around a data-centric approach. It allows you to dive deep into each LF and understand it in detail.

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DataRobot Blog

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

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AWS Machine Learning Blog

MAY 3, 2023

For any machine learning (ML) problem, the data scientist begins by working with data. This includes gathering, exploring, and understanding the business and technical aspects of the data, along with evaluation of any manipulations that may be needed for the model building process.

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Heartbeat

JULY 17, 2023

Make sure that you import Comet library before PyTorch to benefit from auto logging features Choosing Models for Classification When it comes to choosing a computer vision model for a classification task, there are several factors to consider, such as accuracy, speed, and model size. Pre-trained models, such as VGG, ResNet.

Computer Vision 52

Computer Vision Auto-classification Deep Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

Hey guys, in this blog we will see some of the most asked Data Science Interview Questions by interviewers in [year]. Data science has become an integral part of many industries, and as a result, the demand for skilled data scientists is soaring. What is Data Science?

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Heartbeat

MARCH 1, 2023

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. A convolutional neural network (CNN) is primarily used for image classification.

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ODSC - Open Data Science

APRIL 17, 2023

With all the talk about new AI-powered tools and programs feeding the imagination of the internet, we often forget that data scientists don’t always have to do everything 100% themselves. This frees up the data scientists to work on other aspects of their projects that might require a bit more attention.

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Heartbeat

JUNE 26, 2023

Today, I’ll walk you through how to implement an end-to-end image classification project with Lightning , Comet ML, and Gradio libraries. Image Classification for Cancer Detection As we all know, cancer is a complex and common disease that affects millions of people worldwide. This architecture is often used for image classification.

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DataRobot Blog

JUNE 3, 2022

Data Scientists may think the future of AI is GPT-3, and it has created new possibilities in the AI landscape. With limited input text and supervision, GPT-3 auto-generated a complete essay using conversational language peculiar to humans. Quadrant Solutions SPARK Matrix: Data Science and Machine Learning Platform.

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The MLOps Blog

FEBRUARY 27, 2023

He has two master’s degrees in Complex Systems Science from École Polytechnique and the University of Warwick. He has led several data science projects spanning multiple industries like manufacturing, retail, healthcare, insurance, safety, et cetera. Michal is the Director of AI at Deepsense.ai. It’s a process.

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Mlearning.ai

JUNE 28, 2023

This piece of data that my mentor found is called “ SemCor Corpus [5] ” (We access the dataset via NLTK’s SemcorCorpusReader [6] ) The reformatted version of the dataset looks something like this. It might look quite overwhelming but this is what data science and computer engineering are about.

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DataRobot Blog

JANUARY 10, 2023

ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. 42% of data scientists are solo practitioners or on teams of five or fewer people.

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Unite.AI

DECEMBER 1, 2023

In model-centric AI, data scientists or researchers assume the data is static and pour their energy into adjusting model architectures and parameters to achieve better results. Our primary source of signal comes from subject matter experts who collaborate with data scientists to build labeling functions.

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The MLOps Blog

JUNE 27, 2023

Some popular end-to-end MLOps platforms in 2023 Amazon SageMaker Amazon SageMaker provides a unified interface for data preprocessing, model training, and experimentation, allowing data scientists to collaborate and share code easily. It provides a high-level API that makes it easy to define and execute data science workflows.

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Heartbeat

JUNE 27, 2023

They are as follows: Node-level tasks refer to tasks that concentrate on nodes, such as node classification, node regression, and node clustering. Edge-level tasks , on the other hand, entail edge classification and link prediction. Graph-level tasks involve graph classification, graph regression, and graph matching.

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Snorkel AI

JANUARY 11, 2023

Using Snorkel Flow, Pixability leveraged foundation models to build small, deployable classification models capable of categorizing videos across more than 600 different classes with 90% accuracy in just a few weeks. To help brands maximize their reach, they need to constantly and accurately categorize billions of YouTube videos.

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AWS Machine Learning Blog

JULY 31, 2023

It also enables you to evaluate the models using advanced metrics as if you were a data scientist. In this post, we show how a business analyst can evaluate and understand a classification churn model created with SageMaker Canvas using the Advanced metrics tab.

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AWS Machine Learning Blog

MARCH 1, 2023

To solve this problem, we make the ML solution auto-deployable with a few configuration changes. In our case, we used AutoGluon with SageMaker to realize a two-stage prediction, including churn classification and lifetime value regression. Muhyun Kim is a data scientist at Amazon Machine Learning Solutions Lab.

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Flipboard

AUGUST 17, 2023

If you are prompted to choose a kernel, choose Data Science as the image and Python 3 as the kernel, then choose Select. Use SageMaker Feature Store for model training and prediction To use SageMaker Feature store for model training and prediction, open the notebook 5-classification-using-feature-groups.ipynb.

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Heartbeat

JANUARY 25, 2023

Build and deploy your own sentiment classification app using Python and Streamlit Source:Author Nowadays, working on tabular data is not the only thing in Machine Learning (ML). Data formats like image, video, text, etc., Finally, for evaluation, we are using accuracy , precision, and recall scores. #

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AWS Machine Learning Blog

NOVEMBER 16, 2023

The enhanced data contains new data features relative to this example use case. In your application, take time to imagine the diverse set of questions available in your images to help your classification or regression task. In social media platforms, photos could be auto-tagged for subsequent use. in Data Science.

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Heartbeat

DECEMBER 27, 2023

Use Case To drive the understanding of the containerization of machine learning applications, we will build an end-to-end machine learning classification application. The sample data for this project is E-Commerce Shipping data found on Kaggle to predict whether product shipments were delivered on time. Prerequisite Python 3.8

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Dlabs.ai

JANUARY 16, 2023

Kaggle is an online community for data scientists that regularly organizes data science contests. The Mayo Clinic sponsored the Mayo Clinic – STRIP AI competition focused on image classification of stroke blood clot origin. The goal was to classify the blood clot origins in an ischemic stroke.

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AWS Machine Learning Blog

JANUARY 26, 2023

Data scientists train multiple ML algorithms to examine millions of consumer data records, identify anomalies, and evaluate if a person is eligible for credit. This is a common problem that data scientists face when training their models. About the Authors Tristan Miller is a Lead Data Scientist at Best Egg.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

The system is further refined with DistilBERT , optimizing our dialogue-guided multi-class classification process. Additionally, you benefit from advanced features like auto scaling of inference endpoints, enhanced security, and built-in model monitoring. To mitigate the effects of the mistakes, the diversity of demonstrations matter.

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Topbots

JUNE 29, 2023

Figure 1: Representation of the Text2SQL flow As our world is getting more global and dynamic, businesses are more and more dependent on data for making informed, objective and timely decisions. However, as of now, unleashing the full potential of organisational data is often a privilege of a handful of data scientists and analysts.

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AWS Machine Learning Blog

JANUARY 9, 2023

For example, an image classification use case may use three different models to perform the task. The scatter-gather pattern allows you to combine results from inferences run on three different models and pick the most probable classification model. These endpoints are fully managed and support auto scaling.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business needs. This algorithm can handle data that is not linearly separable. This is a binary classification problem. Otherwise, it chooses ensemble mode.

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