Sat.Jan 14, 2023 - Fri.Jan 20, 2023

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What is Data Quality in Machine Learning?

Analytics Vidhya

Introduction Machine learning has become an essential tool for organizations of all sizes to gain insights and make data-driven decisions. However, the success of ML projects is heavily dependent on the quality of data used to train models. Poor data quality can lead to inaccurate predictions and poor model performance. Understanding the importance of data […] The post What is Data Quality in Machine Learning?

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Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation

BAIR

Reinforcement learning provides a conceptual framework for autonomous agents to learn from experience, analogously to how one might train a pet with treats. But practical applications of reinforcement learning are often far from natural: instead of using RL to learn through trial and error by actually attempting the desired task, typical RL applications use a separate (usually simulated) training phase.

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Make data protection a 2023 competitive differentiator

IBM Journey to AI blog

Data privacy regulations, such as the General Data Protection Regulation (GDPR) in the European Union or the California Consumer Privacy Act (CCPA) in the state of California, are inescapable. By 2024, for instance, 75% of the entire world’s population will have its personal data protected by encryption, multifactor authentication, masking and erasure, as well as data resilience.

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Build a free Stable Diffusion app with a GPU backend

AssemblyAI

Stable Diffusion allows you to create incredible images like the one below with only a sentence; but it requires a GPU to run in a reasonable amount of time. Since GPUs are expensive and in short supply, many users opt to instead pay for credits in a web app like DreamStudio in order to use Stable Diffusion in the cloud. Luckily, users do not need to pay for either of these options.

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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Ensemble Learning Methods: Bagging, Boosting and Stacking

Analytics Vidhya

Introduction Machine learning is great! But there’s one thing that makes it even better: ensemble learning. Ensemble learning helps enhance the performance of machine learning models. The concept behind it is simple. Multiple machine learning models are combined to obtain a more accurate model. Bagging, boosting and stacking are the three most popular ensemble learning techniques. […] The post Ensemble Learning Methods: Bagging, Boosting and Stacking appeared first on Analytics Vidhy

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Accelerat.ai: a small data, smart data approach

Defined.ai blog

With its limitless potential to drive future growth , competitiveness, and job creation, AI is predicted to become the competitive advantage of the 21st century. As a result, AI innovation and adoption have emerged as key to international competition in both economic and state applications. Europe remains behind in the AI race According to AI Watch Index , Europe continues to lag behind the US and China in global AI power, despite recent healthy investment growth.

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Clinical Associate Professor of Data Science and Psychology Pascal Wallisch tackles Twitter’s most…

NYU Center for Data Science

Clinical Associate Professor of Data Science and Psychology Pascal Wallisch tackles Twitter’s most pressing questions about visual illusions for Wired The visual perception expert explains the science behind blivets, motion-induced blindness, mirages, the viral dress image, and more Clinical Associate Professor of Data Science and Psychology, Pascal Wallisch When Clinical Associate Professor of Data Science and Psychology Pascal Wallisch received an email from Wired looking for “tech support exp

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Complete Guide to Ethereum Blockchain with Python

Analytics Vidhya

Introduction We have internet access in every corner of the country. Almost all businesses around us, like manufacturing, retail, consultancy, etc., are trying to go digital and display themselves on the web to scale and increase sales. If you want to know anything about your surroundings, then the internet is the first choice we prefer. […]. The post Complete Guide to Ethereum Blockchain with Python appeared first on Analytics Vidhya.

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A Data Scientist Explains: When Does Machine Learning Work Well in Financial Markets?

DataRobot Blog

As a data scientist, one of the best things about working with DataRobot customers is the sheer variety of highly interesting questions that come up. Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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What’s New With SQL User-Defined Functions

databricks

Since their initial release, SQL user-defined functions have become hugely popular among both Databricks Runtime and Databricks SQL customers. This simple yet powerful.

ML 88
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Set up Amazon SageMaker Studio with Jupyter Lab 3 using the AWS CDK

AWS Machine Learning Blog

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models. In Studio, you can load data, adjust ML models, move in between steps to adjust experiments, compare results, and deploy ML models for inference.

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AWS Lambda Tutorial: Creating Your First Lambda Function

Analytics Vidhya

Introduction to AWS AWS, or Amazon Web Services, is one of the world’s most widely used cloud service providers. It is a cloud platform that provides a wide variety of services that can be used together to create highly scalable applications. AWS has many clusters of data centers in multiple countries across the globe. These […]. The post AWS Lambda Tutorial: Creating Your First Lambda Function appeared first on Analytics Vidhya.

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ML Education at Uber: Program Design and Outcomes

Uber AI

If you have read our previous article, ML Education at Uber: Frameworks Inspired by Engineering Principles, you have seen several examples of how Uber benefits from applying Engineering Principles to drive the ML Education Program’s content design and program frameworks. In this follow-up, we will dig deeper into what we believe to be other unique aspects of ML Education at Uber: our approach to Content Components, Content Delivery, Observability, and Marketing & Reach.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Easy Ingestion to Lakehouse With COPY INTO

databricks

A new data management architecture known as the data lakehouse emerged independently across many organizations and use cases to support AI and BI.

AI 93
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Goodbye Roam Research, Hello Obsidian

Eugene Yan

How to migrate and sync notes & images across devices

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Data Science and Artificial Intelligence in 2023 – Difference, Applications, & Job Trajectory

Analytics Vidhya

Introduction Data Science and Artificial Intelligence (AI) are two of the most rapidly growing and exciting technological fields today. Both disciplines are revolutionizing how we process, analyze, and make sense of data to solve complex problems and make informed decisions. In this blog, we will delve into the definitions of Data Science and AI, explore […].

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Churn prediction using multimodality of text and tabular features with Amazon SageMaker Jumpstart

AWS Machine Learning Blog

Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. Understanding customer behavior is top of mind for every business today. Gaining insights into why and how customers buy can help grow revenue. Customer churn is a problem faced by a wide range of companies, from telecommunications to banking, where customers are typically lost to competitors.

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How to Improve Email Deliverability and Optimize Each Send

Learn how to optimize email deliverability and drive greater email ROI. What lands your email in the customer’s inbox? Understanding those factors, otherwise known as email deliverability, is critical to getting the most return on your campaign investments. But the “rules” around which factors land you in the spam folder aren’t always easy to keep up with.

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New Built-in Functions for Databricks SQL

databricks

Built-in functions extend the power of SQL with specific transformations of values for common needs and use cases. For example, the LOG10 function.

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What is Deepfake AI & How do you Identify them?

Pickl AI

The surge of AI and its penetration across the industry and in common lives is evident. If you like to keep pace with the new developments, you would have come across the term Deepfake videos. These videos that look almost similar to the real personality. But the irony is that these videos are fake. With AI, one can create a replica of a celebrity, which is close to reality.

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Unlock Learnings with the January DataHour Sessions!

Analytics Vidhya

Introduction If you are looking for a platform where you can learn about Data Science, then look no more! Analytics Vidhya is the one. We have always kept our community at the centre stage of the ecosystem. In mind, Analytics Vidhya has launched the DataHour sessions, which will improve your domain knowledge and help you […] The post Unlock Learnings with the January DataHour Sessions!

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Using TensorFlow for Deep Learning on Video Data

TensorFlow

Posted by Shilpa Kancharla Video data contains a rich amount of information, and has a more complex and large structure than image data. Being able to classify videos in a memory-efficient way using deep learning can help us better understand the contents within the data. On tensorflow.org, we have published a series of tutorials on how to load, preprocess, and classify video data.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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Prompting and weak supervision to build better, smaller models

Snorkel AI

Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. In the video above, Alex talks with Ryan Smith, Senior Applied Scientist at Snorkel, about the work he did on using foundation models to build compact, deployable, and effective models. Below follows a transcript of their conversation, lightly edited for readability.

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Quantitative Analyst vs Data Scientist: Comparing roles

Pickl AI

Data Science is one of the most in-demand career choices in the present times. From food to finance, every industry is exploring new ways to use data and improvise strategies to reach out to potential customers. Data Scientists play a significant role in this. Hence it has also triggered the demand for Data Science professionals. Today, several platforms are providing Data Science course online.

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Governing Ethical AI: Rules & Regulations Preventing Unethical AI

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Artificial intelligence (AI) is rapidly becoming a fundamental part of our daily lives, from self-driving cars to virtual personal assistants. However, as AI technology advances, it is crucial to consider the ethical implications of its development and use. The use of AI […].

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Model Monitoring for Time Series

The MLOps Blog

Model monitoring is an essential part of the CI/CD pipeline. It ensures consistency and offers robustness to the application that is deployed. One of the major issues with any model is that it may perform well in the development phase, but when deployed, it may perform poorly or may even fail. This is especially true with the time series model, as the changes in the dataset can be quite rapid.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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5 Useful Tips to Write Better Academic Content

How to Learn Machine Learning

Writing assignments, essays, research papers, or other academic write-ups is challenging. It is the phase that every student has to go through in their university or college life. In fields like Artificial Intelligence or Machine Learning , despite its difficulty, it is a must for those that want to go into research. Also, we think that the process of writing content about something lets you unleash this content from your mind and really see if you have understood it or not.

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How to become a Data Scientist in 2023?

Pickl AI

Data Science is the field in which data is collected, analysed and interpreted in order to extract meaningful insights to solve business problems. The field of Data Science is extremely lucrative allowing business organisations to make efficient decisions. Accordingly, the need to evaluate meaningful data for businesses has invoked myriad job opportunities in Data Science.

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Unveiling Financial Insights: A Financial EDA Journey

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Once upon a time, there was an individual trader named Anand. He was a novice in the finance industry, and like many traders, he struggled to find a consistent and profitable trading strategy. Anand was determined to improve his skills and searched […]. The post Unveiling Financial Insights: A Financial EDA Journey appeared first on Analytics Vidhya.