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Towards Data Science

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Anatomy of a Parquet File

Parquet files are produced using PyArrow, which allows for fine-tuned parameter tuning.
Dataframes in Parquet files are stored in a columns-oriented storage format, unlike Pandas' row-wise approach.
Parquet files are commonly stored in object storage databases like S3 or GCS for easy access by data pipelines.
A partitioning strategy organizes Parquet files in directories based on partitioning keys like birth_year and city.
Partition pruning allows query engines to read only necessary files, based on folder names, reducing I/O.
Decoding a raw Parquet file involves identifying the 'PAR1' header, row groups with data, and footer holding metadata.
Parquet uses a hybrid structure, partitioning data into row groups for statistics calculation and query optimization.
Page size in Parquet files is a trade-off, balancing memory consumption and data retrieval efficiency.
Encoding algorithms like dictionary encoding and compression are used for optimizing columnar format in Parquet.
Understanding Parquet's structure aids in making informed decisions on storage strategies and performance optimization.

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Towards Data Science

324

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Fourier Transform Applications in Literary Analysis

Data collection for literary analysis involves gathering information on the number of letters, words, syllables, and visual length of each line by parsing the poem and employing specific algorithms in Python.
Calculating the number of letters in each line involves summing the letter count of each word, while visual length is determined by the total number of characters in the line, assuming a monospace font.
Determining the syllable count in each word is done by identifying vowel clusters, utilizing a function to count syllables in a word and summing the counts for each line.
The data collection algorithm compiles all these operations into a single function, offering a linear time complexity and efficient analysis for large datasets.
Utilizing the discrete Fourier Transform (DFT) in literary analysis requires understanding algorithms like NumPy's fast Fourier transform method and applying it to collected data for frequency analysis.
The Fourier analysis function processes the data, extracts complex coefficients representing amplitude and phase, and returns the Fourier magnitude spectrum for further analysis.
By evaluating the signal-to-noise ratio (SNR) of various metrics like word count, letter count, syllable count, and visual length, patterns and periodic structures in poetry can be revealed.
The SNR analysis unveils relationships between metrics and poem structures, such as rhyme schemes and periodic word patterns, showcasing the potential of mathematical tools in literary exploration.
Through Fourier analysis, hidden patterns in literary works can be uncovered, providing insights into authors' writing styles and presenting a new approach to analyzing formal qualities in literature.
This intersection of mathematics, computer science, data analytics, and literature opens up avenues for broader applications such as stylometry, sentiment analysis, and topic modeling in the realm of data science.

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Tech Radar

283

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I tried Gemini's new AI image generation tool - here are 5 ways to get the best art from Google's Flash 2.0

Gemini Flash 2.0 by Google offers a fast image creation tool with notable speed and quality improvements compared to others like DALL-E 3.
To get the best results from Gemini Flash, telling a story and instructing it to generate a series of related images can be engaging and effective.
Being super specific in your instructions to Gemini Flash can lead to more accurate and detailed image outputs.
Engaging in a conversational style with Gemini Flash allows you to make edits and adjustments to the generated images, enhancing customization.
Gemini Flash's ability to match ChatGPT in terms of real-world knowledge enables users to request historically accurate and culturally detailed imagery.
Utilizing Gemini Flash's efficient text integration feature, users can quickly and clearly incorporate text into generated images.
By following these tips, users can maximize the potential of Google's Gemini Flash 2.0 for creating high-quality and personalized AI-generated art.
Interacting with Gemini Flash through detailed and specific commands can result in images that closely match the envisioned concepts.
Gemini Flash's features like quick text rendering and conversational adjustments make it a versatile tool for creating diverse and customized AI art.
The advancements in AI art generation tools like Gemini Flash showcase the evolving capabilities and possibilities in the field of artificial intelligence and creative applications.

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TechBullion

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6 Benefits of Using Clinical Data Management Software

Clinical data management software (CDMS) is gaining popularity in the healthcare industry due to its potential to streamline data management processes and reduce errors.
One key benefit of CDMS is its ability to prevent mistakes in patient records by using automated checks and alerts to catch inaccuracies before they cause harm.
CDMS helps in organizing workflows, assigning tasks, tracking progress, and providing notifications to ensure efficient coordination among stakeholders in clinical trials.
Digital records in CDMS facilitate quick retrieval of patient information, leading to faster decision-making and more efficient care delivery.
CDMS enhances security measures by utilizing encryption, role-based access, and audit trails to protect sensitive patient data from cyberattacks and unauthorized access.
Compliance with healthcare regulations such as HIPAA and GDPR is critical, and CDMS software is designed with these regulations in mind to maintain data security and patient trust.
Implementing CDMS can result in long-term cost savings for healthcare facilities by reducing the need for paper-based processes, storage, and administrative tasks.
Automating routine administrative tasks through CDMS allows clinical data managers to focus on essential activities like patient care, research, and operational improvements.
CDMS streamlines data handling in clinical trials, improving accuracy and efficiency by eliminating manual processes and reducing the risk of errors.
Considering the various benefits of clinical data management software, organizations can evaluate its potential impact and suitability for their specific needs.

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TechBullion

396

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Standout Crypto Podcast QuickSwap’s “The Aggregated” Nails Century Mark, Sets Stage for Star-Studded Next 100 Episodes!

QuickSwap’s “The Aggregated” recently celebrated its 100th episode, showcasing a unique blend of market insights and positivity amidst a sluggish market in 2025.
The podcast distinguishes itself by featuring top industry figures and thought leaders, offering in-depth analysis, engaging discussions, and a touch of humor.
Originally titled “All Roads Lead to Polygon,” the podcast now covers various blockchain technologies and their impact on industries, aiming to educate and empower the crypto community.
Hosted by the QuickSwap team, “The Aggregated” has gained prominence for its quality content, diverse guests, and loyal following.
The podcast's success lies in its commitment to adapt and provide insights from influential voices such as Bitboy, Crypto Wendy, and many others from different crypto ecosystems.
With a diverse guest lineup, “The Aggregated” offers uncensored access to crucial minds shaping the future of finance and technology.
As it approaches its 200th episode, the podcast remains dedicated to delivering expert insights, discussions, and alpha releases to keep listeners informed.
In a rapidly evolving crypto landscape, QuickSwap’s “The Aggregated” promises to continue providing high-quality content and staying ahead in the realm of Web3 and cryptocurrency.
Listeners can expect the show to offer expert analysis, critical discussions, and unfiltered debates with unbiased perspectives from genuine primary sources.
For those seeking to navigate the changing crypto landscape, QuickSwap’s “The Aggregated” stands as a go-to source for staying informed and ahead in the industry.
As the podcast steps into its next 100 episodes, it remains a crucial platform for understanding and shaping the future of Web3, finance, and technology.

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Medium

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Navigating the Challenges of Vertical (Feature-Focused) Team Structures

Vertical teams, which own complete slices of the product, can lead to advantages such as clear ownership and faster feature delivery.
However, a purely vertical team structure can result in overlapping functionality and duplication of code.
Fragmented ownership and technical debt are also challenges faced by vertical teams.
To mitigate these issues, companies can establish horizontal teams for core functionalities and implement processes for code sharing and architectural consistency.

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Pcgamer

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Microsoft unveils Copilot for Gaming, an AI-powered 'ultimate gaming sidekick' that will let you talk to your console so you don't have to talk to your friends

Microsoft is bringing its AI-powered chatbot assistant Copilot to Xbox as 'Copilot for Gaming'.
The AI aims to help players save time, find new games, and provide coaching and connections with friends.
It can make personalized game recommendations, provide in-game assistance, and suggest character switches.
Copilot for Gaming will also help connect players with families and communities and allow control over interactions.

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TheNewsCrypto

288

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51nodes Partners with World Mobile to Drive RWA Tokenization & DePIN Innovation

51nodes partners with World Mobile to drive RWA tokenization and DePIN innovation by deploying decentralized physical infrastructure solutions and apps using blockchain technology.
The focus is on tokenizing data-based assets in Europe's industrial sector through a $5 million grant program funding fifty initiatives with up to $100,000 each.
51nodes, a German company specializing in blockchain technology integration, will leverage World Mobile Chain to deploy decentralized solutions and apps for data-based tokenized assets in Europe.
The grant projects aim to enhance security, rating mechanisms, and streamline the commercialization of data, inventories, and financial assets across various industries.
Initiatives will establish tokenized asset frameworks while ensuring high security standards for partners in critical infrastructure sectors.
Joint efforts aim to automate industries with blockchain technology, introducing new financial and identification standards like stablecoins and digital corporate identity solutions.
The partnership seeks to expand the market for tokenized data by presenting practical reference models for secure data automation, efficient asset management, and streamlined financial operations.
World Mobile's DePIN network, based on blockchain technology, aims to make global connectivity more accessible through a sharing economy model, allowing individuals and communities to earn rewards by connecting networks.
World Mobile Chain, a Layer 3 blockchain, powers decentralized telecom and DePIN applications, supporting businesses, developers, and communities in building future-generation infrastructure.
The collaboration between 51nodes and World Mobile represents a significant step towards real-world asset tokenization and DePIN solutions, enhancing automation, data monetization, and asset transactions.

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Pymnts

202

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Stablecoin Bill Heads to Senate After Vote in Banking Committee

A stablecoin bill, the GENIUS Act, has been advanced by an 18-6 vote in the Senate Banking Committee and is now headed to the full Senate.
The bill, a priority of President Donald Trump, aims to establish a safe and pro-growth regulatory framework for stablecoins.
The GENIUS Act proposes a regulatory balance between state and federal oversight for stablecoin issuers.
Similar legislation is being worked on by the House Financial Services Committee.

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Towards Data Science

389

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Mastering Hadoop, Part 2: Getting Hands-On — Setting Up and Scaling Hadoop

Hadoop Ozone, a distributed object storage system, was added to the Hadoop architecture in 2020 as an alternative to HDFS for better handling modern data requirements.
HDFS stores files divided into blocks distributed across nodes, replicated three times for data integrity.
Hadoop follows a master-slave principle with NameNode as master and DataNodes storing data blocks.
MapReduce enables parallel processing, with mappers splitting tasks and reducers aggregating results.
YARN manages cluster resources efficiently, separating resource management from data processing.
Hadoop Common provides foundational components for the Hadoop ecosystem for seamless operation of all components.
Hadoop Ozone offers a scalable storage solution optimized for Kubernetes and cloud environments.
Hadoop can be installed locally for single-node testing and can be scaled in a distributed environment.
Hadoop can also be deployed in the cloud with providers offering automated scaling and cost-efficient solutions.
Basic commands in Hadoop enable data storage, processing, and debugging for efficient cluster management.

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Medium

423

How to Use XML Documents as Lookup Tables From Java

This article highlights the use of XPath 2.0 in Java to look up data within XML documents.
The XML file has a element with child elements, each having a key attribute and a nested element.
XPath expressions can be used to map currency keys to their corresponding names or vice versa.
The Java module xpath2.0-helper from Maven Central simplifies the process, allowing for efficient and concise code.

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Towards Data Science

233

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Are You Still Using LoRA to Fine-Tune Your LLM?

LoRA, a method for fine-tuning language models with a smaller set of trainable parameters, has gained popularity and integration into mainstream ML frameworks like Keras.
Researchers are exploring alternatives to LoRA, with a focus on leveraging singular value decomposition (SVD) to select smaller 'adapter' matrices for efficient training.
SVD splits a matrix into three components: U, S, and V, enabling efficient matrix analysis and manipulation.
Several recent SVD-based low-rank fine-tuning techniques have emerged, such as SVF and SVFT, focusing on optimizing matrix singular values for training.
Techniques like PiSSA and MiLoRA propose tuning only specific subsets of singular values to improve fine-tuning efficiency and avoid overfitting.
LoRA-XS represents a variation of these techniques, offering results comparable to PiSSA but with fewer parameters.
Exploration of singular value properties questions the practicality of categorizing them as 'large' and 'small' for fine-tuning purposes.
Transformer models like SVF and SVFT provide parameter-efficient alternatives to LoRA, offering flexibility in tuning while maintaining model performance.
In conclusion, adopting SVD-based techniques like SVF can lead to more efficient fine-tuning processes while achieving desired model outcomes with reduced parameter sets.
Further research is ongoing in the field of low-rank fine-tuning methods to enhance the effectiveness of training large language models.

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Hackernoon

427

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Moonacy Protocol Adds Dogecoin (DOGE) To Its Ecosystem

Moonacy Protocol has added Dogecoin (DOGE) to its ecosystem.
Users of the platform can now utilize DOGE for deposits, exchanges, and withdrawals.
Dogecoin is a popular meme coin with a large crypto community and Elon Musk's backing.
The addition of DOGE to Moonacy Protocol is aimed at expanding the platform's offerings and user-friendly features.

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TheNewsCrypto

351

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Etherlink Unleashes Calypso Upgrade to Accelerate Tezos L2 Development

The Calypso upgrade has provided performance enhancements for Tezos L2 Etherlink in terms of speed, efficiency, and resilience.
Key improvements include lower disk footprint, quicker smart contract storage, and strengthened governance.
The upgrade also enhances stability and enables quicker withdrawals between Etherlink and Tezos.
Etherlink's development will progress with the Calypso upgrade, paving the way for token bridging and interoperability.

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Hackernoon

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Aura Raises $5.5 Million Seed Round To Accelerate AI Model Validation And Rental Marketplace

Aura, a platform for testing, validating, and accessing on-chain AI models, has raised $5.5 million in seed funding.
The funding round was led by Daxos Capital, Manifold Trading, and Selini Capital, with participation from Hermeneutic Investments.
Aura aims to address challenges in the on-chain AI industry, including fragmented model discovery, limited monetization opportunities, and complexity in model selection.
The company has announced strategic partnerships and collaborations with OKX, Virtual Protocol, ElizaOS, GOAT, and others.

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