September, 2024

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How to Manage Your Data Science Project: 7 Top Tips

DagsHub

Source: Unsplash In the high-stakes world of data science and AI, project success is far from guaranteed. As leaders in this field, we're acutely aware of the multifaceted challenges that can derail even the most promising initiatives. From models falling short of requirements to production failures with real-world data, the path to success is fraught with potential pitfalls.

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Exploring the Data Science vs Computer Science Debate

Data Science Dojo

Data science and computer science are two pivotal fields driving the technological advancements of today’s world. In an era where technology has entered every aspect of our lives, from communication and healthcare to finance and entertainment, understanding these domains becomes increasingly crucial. It has, however, also led to the increasing debate of data science vs computer science.

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Understanding Data Collection: Methods, Types, Examples and Tools

Pickl AI

Summary: Data collection is crucial for analysis and decision-making. It includes methods like surveys, interviews, and primary and secondary types. Choosing the right approach ensures reliable, actionable data. Introduction Data collection is crucial in gathering accurate information for decision-making, research, and analysis. It involves systematically obtaining data from various sources using different data collection methods.

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Crack the Code: Mastering Category Encoders for Data Scientists

KDnuggets

Image by Author | Canva In data science, handling different types of data is a daily challenge. One of the most common data types is categorical data, which represents attributes or labels such as colors, gender, or types of vehicles. These characteristics or names can be divided into distinct groups or categories, facilitating classification.

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The 2nd Generation of Innovation Management: A Survival Guide

Speaker: Chris Townsend, VP of Product Marketing, Wellspring

Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?

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Why I Wrote Data Science for Crime Analysis with Python

Hacker News

Data Science | Crime Analysis | python | book

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Data and AI innovation — any way you code it

SAS Software

In a world rich in data, data enthusiasts and problem solvers can have greater success and innovate faster with flexibility in choice. To code or not to code. The answer aligns with the problem and the data talent working to solve it. What does innovation look like inside your organization? [.

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Data Science Agent and Code Transformation

Hacker News

/code in Google Labs contains various code experiments, such as Data Science Agent and Code Transformation.

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How to Make the Most of Data Science Conferences?

Pickl AI

Summary: Data Science conferences provide invaluable opportunities for learning, networking, and career growth. Maximise your experience by researching the agenda, setting goals, engaging in sessions, and following up with contacts post-event. Be well-prepared to gain new insights and skills that can drive your success in Data Science. Introduction Professionals from various industries attend Data Science conferences to discuss Data analysis, innovation, and strategy.

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Preference Learning Algorithms Fail to Learn Human Preference Rankings

NYU Center for Data Science

Language models trained to align with human preferences rarely achieve high ranking accuracy on those same preferences, according to new research from CDS PhD student Angelica Chen and colleagues. Their study reveals fundamental flaws in popular alignment techniques like reinforcement learning from human feedback (RLHF) and direct preference optimization (DPO).

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Innovation vs. Ethical Implementation: Where Does AI Stand Today?

insideBIGDATA

In this contributed article, Vall Herard, CEO of Saifr.ai, discusses AI ethics. With the adoption of AI comes the next phase of innovation: understanding our moral compass and learning how to balance technology with morality — AND compliance.

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Apache Airflow®: The Ultimate Guide to DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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5 Quirky Data Science Projects to Impress

KDnuggets

Develop unique yet standing-out data science projects to improve your data portfolio.

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Media Production with AI: 7 Fields of Creativity in the Industry

Data Science Dojo

In the modern media landscape, artificial intelligence (AI) is becoming a crucial component for different mediums of production. This era of media production with AI will transform the world of entertainment and content creation. By leveraging AI-powered algorithms, media producers can improve production processes and enhance creativity. It offers improved efficiency in editing and personalizing content for users.

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Unleash Your Innovation: Announcing the Databricks Generative AI Startup Challenge with Over $1 Million in Credits, Prizes, and Potential Venture Funding

databricks

The Databricks Generative AI Startup Challenge offers $1M+ in prizes for innovative startups building Generative AI use cases on Databricks. Apply by November 1, 2024!

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Building the Same App across Various Web Frameworks

Eugene Yan

Comparing five implementations built with FastAPI, FastHTML, Next.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Key Challenges and Limitations in AI-Language Models

Analytics Vidhya

Introduction Artificial Intelligence has been cementing its position in workplaces over the past couple of years, with scientists spending heavily on AI research and improving it daily. AI is everywhere, from simple tasks like virtual chatbots to complex tasks like cancer detection. It has even recently replaced several jobs in the industry. This inclusion of […] The post Key Challenges and Limitations in AI-Language Models appeared first on Analytics Vidhya.

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The Good, the Bad, and the Future of Data AI

insideBIGDATA

In this contributed article, Paul Scott-Murphy, chief technology officer at Cirata, discusses key best practices for applying generative AI in today’s enterprises. The key to harnessing the explosion of AI is recognizing the good, bad, and future, letting those influence how and where we securely utilize it. Time invested now in doing this proactively will benefit you and your organization tomorrow.

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7 Steps to Mastering Coding for Data Science

KDnuggets

Are you an aspiring data scientist or early in your data science career? If so, you know that you should use your programming, statistics, and machine learning skills—coupled with domain expertise—to use data to answer business questions. To succeed as a data scientist, therefore, becoming proficient in coding is essential. Especially for handling and analyzing.

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Employer Branding: 3 Effective Ways Using Digital Marketing

Data Science Dojo

HR and digital marketing may seem like two distinct functions inside a company, where HR is mainly focused on internal processes and enhancing employee experience. On the other hand, digital marketing aims more at external communication and customer engagement. However, these two functions are starting to overlap where divisions between them are exceedingly blurring.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Fine-tuning Llama 3.1 with Long Sequences

databricks

Mosaic AI Model Training now supports fine-tuning up to 131K context length for Llama 3.1 models. More efficient training at long sequence lengths is made possible by several optimizations highlighted in this post.

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No Free Lunch in LLM Watermarking: Trade-offs in Watermarking Design Choices

ML @ CMU

Advances in generative models have made it possible for AI-generated text, code, and images to mirror human-generated content in many applications. Watermarking , a technique that embeds information in the output of a model to verify its source, aims to mitigate the misuse of such AI-generated content. Current state-of-the-art watermarking schemes embed watermarks by slightly perturbing probabilities of the LLM’s output tokens, which can be detected via statistical testing during verification.

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GPT-4o vs OpenAI o1: Is the New OpenAI Model Worth the Hype?

Analytics Vidhya

Introduction OpenAI has released its new model based on the much-anticipated “strawberry” architecture. This innovative model, known as o1, enhances reasoning capabilities, allowing it to think through problems more effectively before providing answers. As a ChatGPT Plus user, I had the opportunity to explore this new model firsthand. I’m excited to share my insights on […] The post GPT-4o vs OpenAI o1: Is the New OpenAI Model Worth the Hype?

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Hewlett Packard Enterprise Introduces One-click-deploy AI Applications in HPE Private Cloud AI 

insideBIGDATA

Hewlett Packard Enterprise (NYSE: HPE) announces HPE Private Cloud AI is available to order and introduces new solution accelerators to automate and streamline artificial intelligence (AI) applications. HPE Private Cloud AI is a turnkey, cloud-based experience co-developed with NVIDIA to help businesses of every size build and deploy generative AI (GenAI) applications that was introduced as part of the NVIDIA AI Computing by HPE portfolio.

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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10 Built-In Python Modules Every Data Engineer Should Know

KDnuggets

Interested in data engineering? Check out this round-up of built-in Python modules that'll come in handy for data engineering tasks.

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What is a Confusion Matrix? Understand the 4 Key Metric of its Interpretation

Data Science Dojo

In the world of machine learning, evaluating the performance of a model is just as important as building the model itself. One of the most fundamental tools for this purpose is the confusion matrix. This powerful yet simple concept helps data scientists and machine learning practitioners assess the accuracy of classification algorithms , providing insights into how well a model is performing in predicting various classes.

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Introducing Meta Llama 3.2 on Databricks: faster language models and powerful multi-modal models

databricks

We are excited to partner with Meta to launch the latest models in the Llama 3 series on the Databricks Data Intelligence Platform.

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What Does A Data Engineer Do?

Adrian Bridgwater for Forbes

What Is A Data Engineer? It’s a moving definition really, because the role of the data engineer itself is changing.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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How to Access OpenAI o1?

Analytics Vidhya

Introduction Strawberry is out in the market!!! I hope this will be as fruitful as the recent advancements in artificial intelligence brought by other OpenAI’s latest models. We have been waiting for GPT-5 for so long, and now OpenAI has released its fact-checking and high reasoning model—OpenAI o1, with a code name of Strawberry. This […] The post How to Access OpenAI o1?

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insideAI News – Company Highlights for AI Hardware and Edge AI Summit 2024

insideBIGDATA

insideAI News is pleased to announce being a Media Partner for the upcoming AI Hardware & Edge AI Summit happening Sept. 9-12, 2024 in San Jose, Calif. Register now using the special insideAI News discount code “Insideai15” HERE. Editor-in-Chief & Resident Data Scientist, Daniel D.

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10 GitHub Repositories to Master Computer Vision

KDnuggets

The GitHub repository includes up-to-date learning resources, research papers, guides, popular tools, tutorials, projects, and datasets.

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Rethinking LLM Memorization

ML @ CMU

Introduction A central question in the discussion of large language models (LLMs) concerns the extent to which they memorize their training data versus how they generalize to new tasks and settings. Most practitioners seem to (at least informally) believe that LLMs do some degree of both: they clearly memorize parts of the training data—for example, they are often able to reproduce large portions of training data verbatim [ Carlini et al., 2023 ]—but they also seem to learn from this data, allow

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.