The generative AI market faces challenges in defining its business model, balancing between being a product or feature, and sustaining high costs while ensuring meaningful innovation and research.
In 2024, I revamped my data science portfolio using mkdocs for improved aesthetics and functionality, integrating Google Analytics, with a focus on minimal configuration and free solutions.
This article describes using large language models for parsing scientific research papers. It outlines a structured workflow, metadata extraction process, necessary libraries, and code implementation details for efficient document processing.
This guide demonstrates building a simple neural network using TensorFlow and PyTorch to predict ice cream revenue based on temperature and day, emphasising data preparation, model training, and evaluation.
The author shared six SQL optimisation tips, reducing Snowflake query time by 50 hours daily. Key strategies include selecting necessary columns, analysing query profiles, and utilising Snowflake’s functionality effectively.
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---title: "Daily Financial Insights 02.08.2024: Generative AI Business Models, Enhanced Data Science Portfolios, and Efficient SQL Optimization Techniques"page-layout: fulltitle-block-banner: truedate: 08-02-2024categories: [ai,coding,data-science]tags: [ai, business, portfolio, data, models, neural, revenue, sql, optimisation, research]image: /pictures/flat-lay-office-desk-with-laptop-notebook-pencil.jpg---::: {layout-ncol=2}:::{#first-column}In today's curation, we explore a variety of topics pertinent to the intersection of technology and finance:- Challenges in the generative AI market regarding business models and costs- Enhancements made to a data science portfolio using mkdocs and Google Analytics- Utilizing large language models for efficient parsing of scientific papers- Building a simple neural network with TensorFlow and PyTorch for revenue prediction- Six SQL optimization tips for improved performance in Snowflake Please find the details in the table below.::::::{#second-column}![Coffee with daily news](/pictures/flat-lay-office-desk-with-laptop-notebook-pencil.jpg)::::::# AI and Gen-AI| Title | Summary ||-----|-----------|| [Can Generative AI Sustain Its Costly Growth Without Compromising Innovation and Ethical Standards? (Towards Data Science, 2024-08-01)](https://towardsdatascience.com/economics-of-generative-ai-75f550288097) | The generative AI market faces challenges in defining its business model, balancing between being a product or feature, and sustaining high costs while ensuring meaningful innovation and research. |# Coding| Title | Summary ||-----|-----------|| [Effortlessly Build a Stunning Data Science Portfolio with Python and MkDocs: A Step-by-Step Guide (Medium, 2024-08-02)](https://towardsdatascience.com/full-guide-to-build-a-professionnal-portfolio-with-python-markdown-git-and-github-page-for-66d12f7859f0) | In 2024, I revamped my data science portfolio using mkdocs for improved aesthetics and functionality, integrating Google Analytics, with a focus on minimal configuration and free solutions. || [Harnessing the Power of AI for Effortless Scientific Paper Analysis and Metadata Extraction (Medium, 2024-08-02)](https://towardsdatascience.com/document-parsing-using-large-language-models-with-code-9229fda09cdf) | This article describes using large language models for parsing scientific research papers. It outlines a structured workflow, metadata extraction process, necessary libraries, and code implementation details for efficient document processing. || [Effortless Neural Network Building for Beginners: A Practical Guide Using TensorFlow and PyTorch (Deep Learning Illustrated, 2024-08-02)](https://towardsdatascience.com/implementing-neural-networks-in-tensorflow-and-pytorch-3c1f097e412a) | This guide demonstrates building a simple neural network using TensorFlow and PyTorch to predict ice cream revenue based on temperature and day, emphasising data preparation, model training, and evaluation. |# Data, Databases and Data Science| Title | Summary ||-----|-----------|| [Cut Snowflake Query Times by 50 Hours with These Six Simple SQL Hacks for Faster Data Analysis (The name of the blog or website is Snowflake., 2024-08-02)](https://towardsdatascience.com/mastering-sql-optimization-from-functional-to-efficient-queries-74d8692f10be) | The author shared six SQL optimisation tips, reducing Snowflake query time by 50 hours daily. Key strategies include selecting necessary columns, analysing query profiles, and utilising Snowflake's functionality effectively. |