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Top 7 data science, AI and large language models blogs of 2023

Data Science Dojo

In this blog, we will explore the top 7 blogs of 2023 that have been instrumental in disseminating detailed and updated information in these dynamic fields. These blogs stand out not just for their depth of content but also for their ability to make complex topics accessible to a broader audience.

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Data Wrangling with Python

Mlearning.ai

The goal of data cleaning, the data cleaning process, selecting the best programming language and libraries, and the overall methodology and findings will all be covered in this post. Data wrangling requires that you first clean the data. Getting Started First, we need to import the necessary libraries.

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Data Science Dojo - Untitled Article

Data Science Dojo

7 types of statistical distributions with practical examples Statistical distributions help us understand a problem better by assigning a range of possible values to the variables, making them very useful in data science and machine learning. Here are 7 types of distributions with intuitive examples that often occur in real-life data.

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Image Inference through Multi-Modal LLM Models

Towards AI

This blog explores the capabilities of multi-modal models in image inference, highlighting their ability to integrate visual and textual information for improved analysis This member-only story is on us. The emergence of multimodal AI has significantly transformed the landscape of data wrangling. Upgrade to access all of Medium.

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Check out the brand-new SDXL 1.0 and its capabilities

Dataconomy

Clipdrop GitHub Stability AI API AWS Sagemaker AWS Bedrock Stable Foundation Discord DreamStudio Here is an example included in the blog post by Stability AI ( Image Credit ) What is new with SDXL 1.0? Custom LoRAs or checkpoints can be generated with less need for data wrangling. Here is how to get started with SDXL 1.0:

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Teaching with DrivenData Competitions

DrivenData Labs

DrivenData Competitions to use: Any competition with open data Skill options: Flexible to fit a huge range of data science or statistical skills Assessment: Grades can be based on model performance, or a submitted report or presentation. Difficulty: All skill levels.

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State of Machine Learning Survey Results Part One

ODSC - Open Data Science

In a series of articles, we’d like to share the results so you too can learn more about what the data science community is doing in machine learning. In the first blog, we’re going to discuss the technical side of things, such as what languages and platforms people are using. What areas of machine learning are you interested in?