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MLOps and the evolution of data science

IBM Journey to AI blog

Today, 35% of companies report using AI in their business, which includes ML, and an additional 42% reported they are exploring AI, according to the IBM Global AI Adoption Index 2022. MLOps is the next evolution of data analysis and deep learning. How MLOps will be used within the organization.

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2024 Tech breakdown: Understanding Data Science vs ML vs AI

Pickl AI

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation.

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MakeBlobs + Fictional Synthetic Data, Adding Data to Domain-Specific LLMs, and What Tech Layoffs…

ODSC - Open Data Science

8 Tools to Protect Sensitive Data from Unintended Leakage In order to protect themselves from unintended leakage of sensitive information, organizations employ a variety of tools that scan repositories and code continuously to identify the secrets that are hard-coded within. Use our guide to help you ask the right questions to get you in.

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

Its goal is to help with a quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Apache Superset GitHub | Website Apache Superset is a must-try project for any ML engineer, data scientist, or data analyst.

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Up Your Machine Learning Game With These ODSC East 2024 Sessions

ODSC - Open Data Science

By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows. Using Graphs for Large Feature Engineering Pipelines Wes Madrigal | ML Engineer | Mad Consulting Feature engineering from raw entity-level data is complex, but there are ways to reduce that complexity.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Google Cloud Vertex AI Google Cloud Vertex AI provides a unified environment for both automated model development with AutoML and custom model training using popular frameworks. Qwak Qwak is a fully-managed, accessible, and reliable ML platform to develop and deploy models and monitor the entire machine learning pipeline.

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Where AI is headed in the next 5 years?

Pickl AI

Robotics also witnessed advancements, with AI-powered robots becoming more capable in navigation, manipulation, and interaction with the physical world. Explainable AI and Ethical Considerations (2010s-present): As AI systems became more complex and influential, concerns about transparency, fairness, and accountability arose.