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The Three Big Announcements by Databricks AI Team in June 2024

Marktechpost

Table Search and Filtering: Integrated search and filtering functionalities allow users to find specific columns or values and filter data to spot trends and identify essential values. Enhanced Python Features: New Python coding capabilities include an interactive debugger, error highlighting, and enhanced code navigation features.

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#54 Things are never boring with RAG! Vector Store, Vector Search, Knowledge Base, and more!

Towards AI

Python = Powerful AI Research Agent By Gao Dalie () This article details building a powerful AI research agent using Pydantic AI, a web scraper (Tavily), and Llama 3.3. It emphasizes the role of LLamaindex in building RAG systems, managing data ingestion, indexing, and querying. If this sounds exciting, connect in the thread!

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., This includes features for data labeling, data versioning, data augmentation, and integration with popular data storage systems.

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Level Up Your AI Game with More ODSC West Announced Sessions

ODSC - Open Data Science

Streamlining Unstructured Data for Retrieval Augmented Generatio n Matt Robinson | Open Source Tech Lead | Unstructured Learn about the complexities of handling unstructured data, and practical strategies for extracting usable text and metadata from it. You’ll also discuss loading processed data into destination storage.

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Build Data Pipelines: Comprehensive Step-by-Step Guide

Pickl AI

Handling Missing Data: Imputing missing values or applying suitable techniques like mean substitution or predictive modelling. Tools such as Python’s Pandas library, Apache Spark, or specialised data cleaning software streamline these processes, ensuring data integrity before further transformation.

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10 Best Data Engineering Books [Beginners to Advanced]

Pickl AI

The key sectors where Data Engineering has a major contribution include IT, Internet/eCommerce, and Banking & Insurance. Salary of a Data Engineer ranges between ₹ 3.1 Data Storage: Storing the collected data in various storage systems, such as relational databases, NoSQL databases, data lakes, or data warehouses.

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Snorkel AI partners with Snowflake to bring data-centric AI to the Snowflake Data Cloud

Snorkel AI

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models, then scale this knowledge to label large quantities of data.