Sat.Aug 24, 2019 - Fri.Aug 30, 2019

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Building Tools And Platforms For Data Analytics

Data Engineering Podcast

Summary Data engineers are responsible for building tools and platforms to power the workflows of other members of the business. Each group of users has their own set of requirements for the way that they access and interact with those platforms depending on the insights they are trying to gather. Benn Stancil is the chief analyst at Mode Analytics and in this episode he explains the set of considerations and requirements that data analysts need in their tools and.

Building 100
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Types of Bias in Machine Learning

KDnuggets

The sample data used for training has to be as close a representation of the real scenario as possible. There are many factors that can bias a sample from the beginning and those reasons differ from each domain (i.e. business, security, medical, education etc.).

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Is Finance Holding Back Your Bank’s Digital Transformation?

Teradata

How can a Digital CFO break down the silos in the Bank and support the digital agenda in transforming the customer journey? Read more from our experts!

Finance 53
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Using Graph Processing for Kafka Stream Visualizations

Confluent

We know that Apache Kafka ® is great when you’re dealing with streams, allowing you to conveniently look at streams as tables. Stream processing engines like KSQL furthermore give you the ability to manipulate all of this fluently. But what about when the relationships between items dominate your application? For example, in a social network, understanding the network means we need to look at the friend relationships between people.

Kafka 55
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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Using Tableau with DynamoDB: How to Build a Real-Time SQL Dashboard on NoSQL Data

Rockset

In this blog, we examine DynamoDB reporting and analytics, which can be challenging given the lack of SQL and the difficulty running analytical queries in DynamoDB. We will demonstrate how you can build an interactive dashboard with Tableau, using SQL on data from DynamoDB, in a series of easy steps, with no ETL involved. DynamoDB is a widely popular transactional primary data store.

NoSQL 40
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Why Data Visualization Is The Most Important Skill in a Data Analyst Arsenal

KDnuggets

Visually-displayed data is much more accessible, and it’s criticalto promptly identify the weaknesses of an organization, accurately forecasttrading volumes and sale prices, or make the right business choices.

Data 122

More Trending

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Confluent Cloud Schema Registry is Now Generally Available

Confluent

We are excited to announce the release of Confluent Cloud Schema Registry in general availability (GA), available in Confluent Cloud , our fully managed event streaming service based on Apache Kafka ®. Before we dive into Confluent Cloud Schema Registry, let’s recap what Confluent Schema Registry is and does. Confluent Schema Registry provides a serving layer for your metadata and a RESTful interface for storing and retrieving Avro schemas.

Cloud 18
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3 cost-cutting tips for Amazon DynamoDB

Rockset

Amazon DynamoDB is a managed NoSQL database in the AWS cloud that delivers a key piece of infrastructure for use cases ranging from mobile application back-ends to ad tech. DynamoDB is optimized for transactional applications that need to read and write individual keys but do not need joins or other RDBMS features. For this subset of requirements, DynamoDB offers a way to have a virtually infinitely scalable datastore that requires minimal maintenance.

NoSQL 40
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Deep Learning Next Step: Transformers and Attention Mechanism

KDnuggets

With the pervasive important of NLP in so many of today's applications of deep learning, find out how advanced translation techniques can be further enhanced by transformers and attention mechanisms.

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R Users’ Salaries from the 2019 Stackoverflow Survey

KDnuggets

Let’s take a look on what R users are saying about their salaries. Note that the following results could be biased because of unrepresentative and in some cases small samples.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Emoji Analytics

KDnuggets

Emoji is becoming a global language understandable by anyone who expresses. emotion. With the pervasiveness of these little Unicode blocks, we can perform analytics on their use throughout social media to gain insight into sentiments around the world.

Media 116
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The secret sauce for growing from a data analyst to a data scientist

KDnuggets

Despite the increasing demand and appetite for experienced data scientists, the job is ambiguously described most of the times. Also, the delineation between data science and data analytics or engineering is still loosely defined by a lot of hiring managers.

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TensorFlow 2.0: Dynamic, Readable, and Highly Extended

KDnuggets

With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.

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Object-oriented programming for data scientists: Build your ML estimator

KDnuggets

Implement some of the core OOP principles in a machine learning context by building your own Scikit-learn-like estimator, and making it better.

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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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Introducing AI Explainability 360: A New Toolkit to Help You Understand what Machine Learning Models are Doing

KDnuggets

Recently, AI researchers from IBM open sourced AI Explainability 360, a new toolkit of state-of-the-art algorithms that support the interpretability and explainability of machine learning models.

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New Poll: Data Science Skills

KDnuggets

New KDnuggets poll asks 1) What Data Science/Machine Learning-related skills you currently have, and 2) Which skills you want to add or improve? If you are human, please vote and we will analyze and publish the results.

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Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference?

KDnuggets

Over the past few years, artificial intelligence continues to be one of the hottest topics. And in order to work effectively with it, you need to understand its constituent parts.

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4 Tips for Advanced Feature Engineering and Preprocessing

KDnuggets

Techniques for creating new features, detecting outliers, handling imbalanced data, and impute missing values.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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How to count Big Data: Probabilistic data structures and algorithms

KDnuggets

Learn how probabilistic data structures and algorithms can be used for cardinality estimation in Big Data streams.

Algorithm 114
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How to Sell Your Boss on the Need for Data Analytics

KDnuggets

Here are some ways you can make the case to your boss that analytics investments are smart for your company to pursue.

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A 2019 Guide to Human Pose Estimation

KDnuggets

Human pose estimation refers to the process of inferring poses in an image. Essentially, it entails predicting the positions of a person’s joints in an image or video. This problem is also sometimes referred to as the localization of human joints.

Process 81
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Get KDnuggets Pass to Strata Data or TensorFlow World

KDnuggets

As a media partner for O'Reilly, KDnuggets is pleased to offer to our readers a chance to win a 2-day Bronze Conference pass to either Strata Data NYC or TensorFlow in Santa Clara. Enter by Sep 8, 2019.

Media 69
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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Top KDnuggets tweets, Aug 21-27: Algorithms Notes for Professionals – Free Book

KDnuggets

Algorithms Notes for Professionals - Free Book; 10 simple Linux tips which save 50% of my time in the command line; Why so many #DataScientists are leaving their jobs; Order Matters: Alibaba Transformer-based Recommender System.

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Top Stories, Aug 19-25: Top Handy SQL Features for Data Scientists; Nothing but NumPy: Understanding & Creating Neural Networks with Computational Graphs from Scratch

KDnuggets

Also: Deep Learning for NLP: Creating a Chatbot with Keras!; Understanding Decision Trees for Classification in Python; How to Become More Marketable as a Data Scientist; Is Kaggle Learn a Faster Data Science Education?

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KDnuggets™ News 19:n32, Aug 28: Handy SQL Features for Data Scientists; Nothing but NumPy: Creating Neural Networks with Computational Graphs

KDnuggets

Most useful SQL features for Data Scientist; Excellent tutorial on creating neural nets from scratch with Numpy; TensorFlow 2.0 highlights, explained; How to sell your boss on Data Analytics; and more.

SQL 47
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The Death of Centralized AI and the Rise of Open AI

KDnuggets

Centralized AI is giving way to more democratic AI systems, which are becoming more and more accessible to data scientists, both through code and through open ecosystems.

Coding 115
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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.