2022

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What Can AI-Powered RPA and IA Mean For Businesses?

KDnuggets

RPA and IA have stunned the business world by availing impressive, intelligent automation capabilities for scales of businesses across industries, which we'll know in this blog.

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Building a Telegram Bot Powered by Apache Kafka and ksqlDB

Confluent

ksqlDB use case: see how apps can use ksqlDB to ingest, filter, enrich, aggregate, and query data directly with Kafka—no complex architectures or data stores needed.

Kafka 144
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Telco 5G Returns Will Come from Enterprise Data Solutions

Cloudera

This blog post was written by Dean Bubley , industry analyst, as a guest author for Cloudera. . Communications service providers (CSPs) are rethinking their approach to enterprise services in the era of advanced wireless connectivity and 5G networks, as well as with the continuing maturity of fibre and Software-Defined Wide Area Network (SD-WAN) portfolios. .

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Seeing through hardware counters: a journey to threefold performance increase

Netflix Tech

By Vadim Filanovsky and Harshad Sane In one of our previous blogposts, A Microscope on Microservices we outlined three broad domains of observability (or “levels of magnification,” as we referred to them)?—?Fleet-wide, Microservice and Instance. We described the tools and techniques we use to gain insight within each domain. There is, however, a class of problems that requires an even stronger level of magnification going deeper down the stack to introspect CPU microarchitecture.

Bytes 145
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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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7 Techniques to Handle Imbalanced Data

KDnuggets

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

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The Complete Collection of Data Science Books – Part 2

KDnuggets

Read the best books on Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, MLOps, Robotics, IoT, AI Products Management, and Data Science for Executives.

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More Data Science Cheatsheets

KDnuggets

It's time again to look at some data science cheatsheets. Here you can find a short selection of such resources which can cater to different existing levels of knowledge and breadth of topics of interest.

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How To Overcome The Fear of Math and Learn Math For Data Science

KDnuggets

Many aspiring Data Scientists, especially when self-learning, fail to learn the necessary math foundations. These recommendations for learning approaches along with references to valuable resources can help you overcome a personal sense of not being "the math type" or belief that you "always failed in math.".

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We Don’t Need Data Scientists, We Need Data Engineers

KDnuggets

As more people are entering the field of Data Science and more companies are hiring for data-centric roles, what type of jobs are currently in highest demand? There is so much data in the world, and it just keeps flooding in, it now looks like companies are targeting those who can engineer that data more than those who can only model the data.

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How I Got 4 Data Science Offers and Doubled My Income 2 Months After Being Laid Off

KDnuggets

In this blog, I shared my story on getting 4 data science job offers including Airbnb, Lyft and Twitter after being laid off. Any data scientist who was laid off due to the pandemic or who is actively looking for a data science position can find something here to which they can relate.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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How to Select Rows and Columns in Pandas Using [ ],loc, iloc,at and.iat

KDnuggets

Subset selection is one of the most frequently performed tasks while manipulating data. Pandas provides different ways to efficiently select subsets of data from your DataFrame.

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How Much Math Do You Need in Data Science?

KDnuggets

There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.

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Introduction to Pandas for Data Science

KDnuggets

The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.

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If I Had To Start Learning Data Science Again, How Would I Do It?

KDnuggets

While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.

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Building Your BI Strategy: How to Choose a Solution That Scales and Delivers

Speaker: Evelyn Chou

Choosing the right business intelligence (BI) platform can feel like navigating a maze of features, promises, and technical jargon. With so many options available, how can you ensure you’re making the right decision for your organization’s unique needs? 🤔 This webinar brings together expert insights to break down the complexities of BI solution vetting.

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Easy Guide To Data Preprocessing In Python

KDnuggets

Preprocessing data for machine learning models is a core general skill for any Data Scientist or Machine Learning Engineer. Follow this guide using Pandas and Scikit-learn to improve your techniques and make sure your data leads to the best possible outcome.

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Frameworks for Approaching the Machine Learning Process

KDnuggets

This post is a summary of 2 distinct frameworks for approaching machine learning tasks, followed by a distilled third. Do they differ considerably (or at all) from each other, or from other such processes available?

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Free MIT Courses on Calculus: The Key to Understanding Deep Learning

KDnuggets

Calculus is the key to fully understanding how neural networks function. Go beyond a surface understanding of this mathematics discipline with these free course materials from MIT.

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Sparse Matrix Representation in Python

KDnuggets

Leveraging sparse matrix representations for your data when appropriate can spare you memory storage. Have a look at the reasons why, see how to create sparse matrices in with Python, and compare the memory requirements for standard and sparse representations of the same data.

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Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.

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How to Build a Data Science Enablement Team: A Complete Guide

KDnuggets

A Data Science Enablement Team consists of people from various departments like marketing, sales, product development, etc. They are responsible for providing the necessary tools and resources to help the data scientists do their job more efficiently.

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The ABCs of NLP, From A to Z

KDnuggets

There is no shortage of tools today that can help you through the steps of natural language processing, but if you want to get a handle on the basics this is a good place to start. Read about the ABCs of NLP, all the way from A to Z.

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10 Cheat Sheets You Need To Ace Data Science Interview

KDnuggets

The only cheat you need for a job interview and data professional life. It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets.

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More Performance Evaluation Metrics for Classification Problems You Should Know

KDnuggets

When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results. That's where these additional performance evaluations come into play to help tease out more meaning from your model.

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What Is Entity Resolution? How It Works & Why It Matters

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.

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Data Representation for Natural Language Processing Tasks

KDnuggets

In NLP we must find a way to represent our data (a series of texts) to our systems (e.g. a text classifier). As Yoav Goldberg asks, "How can we encode such categorical data in a way which is amenable for us by a statistical classifier?" Enter the word vector.

Process 159
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SQL vs NoSQL: 7 Key Takeaways

KDnuggets

People assume that NoSQL is a counterpart to SQL. Instead, it’s a different type of database designed for use-cases where SQL is not ideal. The differences between the two are many, although some are so crucial that they define both databases at their cores.

NoSQL 160
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Key-Value Databases, Explained

KDnuggets

Among the four big NoSQL database types, key-value stores are probably the most popular ones due to their simplicity and fast performance. Let’s further explore how key-value stores work and what are their practical uses.

Database 159
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What Does ETL Have to Do with Machine Learning?

KDnuggets

ETL during the process of producing effective machine learning algorithms is found at the base - the foundation. Let’s go through the steps on how ETL is important to machine learning.

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Enhance Customer Value: Unleash Your Data’s Potential

The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. With Logi Symphony, we aim to turn these challenges into opportunities. Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights.

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The Complete Free PyTorch Course for Deep Learning

KDnuggets

Do you want to learn PyTorch for machine learning and deep learning? Check out this 24 hour long video course with accompanying notes and courseware for free. Did I mention it's free?

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The Importance of Experiment Design in Data Science

KDnuggets

Do you feel overwhelmed by the sheer number of ideas that you could try while building a machine learning pipeline? You can not take the liberty of trying all possible ways to arrive at a solution - hence we discuss the importance of experiment design in data science projects.

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Top 10 Data Science Myths Busted

KDnuggets

The data science field is full of job opportunities, yet there is still a lot of confusion about what data scientists actually do. This confusion is largely due to the many myths that exist about the role of a data scientist. In this article, we will bust the top 10 myths about data science. By the end of this article, you will have a better understanding of the role of a data scientist and what it takes to be one.

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The AIoT Revolution: How AI and IoT Are Transforming Our World

KDnuggets

The AIoT has the potential to transform industries and society, and it is already starting to have an impact. This article will explore the principles of AIoT, its benefits, and its current use.

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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.