Pickl AI

APRIL 19, 2023

Machine Learning is the part of Artificial Intelligence and computer science that emphasizes on the use of data and algorithms, imitating the way humans learn and improving accuracy. Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Consequently.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

Chatbots Life

MAY 12, 2023

We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers? Will ChatGPT replace ML Engineers? Although the model acts as a highly-skilled, the profession definitely carries a lot of risks. What is ChatGPT capable of?

ChatGPT 90

ChatGPT Software Engineer NLP ML Engineer 90

Pickl AI

JANUARY 29, 2024

Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Key takeaways Data Science lays the groundwork for Machine Learning, providing curated datasets for ML algorithms to learn and make predictions. Emphasises programming skills, understanding of algorithms, and expertise in Data Analysis.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

AWS Machine Learning Blog

FEBRUARY 12, 2024

The Ranking team at Booking.com plays a pivotal role in ensuring that the search and recommendation algorithms are optimized to deliver the best results for their users. This dual-repository approach allows for greater modularity, and enables science and engineering teams to iterate independently on ML code and ML pipeline components.

ML 127

ML Explainability Machine Learning Deep Learning 127

AWS Machine Learning Blog

AUGUST 1, 2023

To start working with a model to learn about the capabilities of ML, all you need to do is open SageMaker Studio, find a pre-trained model you want to use in the Hugging Face Model Hub , and choose SageMaker as your deployment method. No ML engineering experience required. It’s as easy as that!

ML 83

ML Large Language Models NLP Machine Learning 83

Snorkel AI

OCTOBER 12, 2023

In this session, Snorkel AI ML Engineer Ashwini Ramamoorthy explores how data-centric AI can be leveraged to simplify and streamline this process. Columbia PhD student Zachary Huang presents JoinBoost, a lightweight Python library that transforms tree training algorithms over normalized databases into pure SQL queries.

Data Scientist 64

Data Scientist ML Computer Vision AI 64

Snorkel AI

OCTOBER 12, 2023

In this session, Snorkel AI ML Engineer Ashwini Ramamoorthy explores how data-centric AI can be leveraged to simplify and streamline this process. Columbia PhD student Zachary Huang presents JoinBoost, a lightweight Python library that transforms tree training algorithms over normalized databases into pure SQL queries.

Data Scientist 59

Data Scientist ML Computer Vision AI 59

AWS Machine Learning Blog

NOVEMBER 9, 2023

We build a model to predict the severity (benign or malignant) of a mammographic mass lesion trained with the XGBoost algorithm using the publicly available UCI Mammography Mass dataset and deploy it using the MLOps framework. Under Advanced Project Options , for Definition , select Pipeline script from SCM. For SCM , choose Git.

Data Drift 116

Data Drift Auto-complete ML Automation 116

Snorkel AI

OCTOBER 12, 2023

In this session, Snorkel AI ML Engineer Ashwini Ramamoorthy explores how data-centric AI can be leveraged to simplify and streamline this process. Columbia PhD student Zachary Huang presents JoinBoost, a lightweight Python library that transforms tree training algorithms over normalized databases into pure SQL queries.

Data Scientist 52

Data Scientist NLP ML Computer Vision 52

The MLOps Blog

JULY 18, 2023

You need to have a structured definition around what you’re trying to do so your data annotators can label information for you. In our early days, we definitely landed on the notion that there are really two critical pieces to all meeting notes. We like to call these change point detection algorithms.

Conversational AI 52

Conversational AI Natural Language Processing Machine Learning AI 52

The MLOps Blog

AUGUST 3, 2023

This is Piotr Niedźwiedź and Aurimas Griciūnas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. I term it as a feature definition store. I also recently found out, you are the CEO of DAGWorks.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

MARCH 15, 2023

The system used advanced analytics and mostly classic machine learning algorithms to identify patterns and anomalies in claims data that may indicate fraudulent activity. For an experienced Data Scientist/ML engineer, that shouldn’t come as so much of a problem.

ETL 52

ETL Data Drift Machine Learning ML 52

The MLOps Blog

MARCH 21, 2023

As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale. In this comprehensive guide, we’ll explore everything you need to know about machine learning platforms, including: Components that make up an ML platform.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Unite.AI

FEBRUARY 22, 2024

The very definition of ethical AI is subjective, giving rise to crucial questions about who should have the authority to decide what constitutes Responsible AI. By mitigating biases and fostering an inclusive approach, organizations can avoid pitfalls such as discriminatory algorithms in areas like recruiting.

Responsible AI 274

Responsible AI Explainability AI AI 274

AWS Machine Learning Blog

NOVEMBER 29, 2023

Customers can select relevant evaluation datasets and metrics for their scenarios and extend them with their own prompt datasets and evaluation algorithms. As a fully-managed service, SageMaker Clarify simplifies the use of open-source evaluation frameworks within Amazon SageMaker. temperature: 0.6 name: "llama2-7b-finetuned".

LLM 99

LLM Data Scientist Algorithm Generative AI 99

The MLOps Blog

DECEMBER 29, 2022

Navigating through current ML frameworks Stephen: Right. Kyle, you definitely touched upon this already. Pietra, in chat, also notes that before ML frameworks like TensorFlow, you had to go really low-level and code in a native CUDA. Kyle: Yes, I can speak that you definitely can. So, you definitely can.

ML 52

ML Machine Learning Auto-complete Python 52