Sat.Dec 24, 2022 - Fri.Dec 30, 2022

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Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science

KDnuggets

Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.

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Understanding BigQuery: Architecture and Use Case

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: Author(Paint) Introduction Arushi is a data architect in a company named Redeem. The company provides cashback to customers who check in at restaurants & hotels. Customers log in through the app and upload the bills and they got a certain percentage of […]. The post Understanding BigQuery: Architecture and Use Case appeared first on Analytics Vidhya.

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Building a Logistic Regression Classifier in PyTorch

Machine Learning Mastery

Last Updated on December 30, 2022 Logistic regression is a type of regression that predicts the probability of an event. It is used for classification problems and has many applications in the fields of machine learning, artificial intelligence, and data mining. The formula of logistic regression is to apply a sigmoid function to the output […] The post Building a Logistic Regression Classifier in PyTorch appeared first on MachineLearningMastery.com.

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A match made in transportation heaven: AI and self-driving cars

Dataconomy

Artificial intelligence (AI) has the potential to revolutionize the way we drive and transport goods and people. Self-driving cars, also known as autonomous vehicles, are a type of vehicle that use AI and other advanced technologies to navigate roads and highways without the need for a human driver. There are several benefits to self-driving cars. […].

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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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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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Knowledge Enhanced Machine Learning: Techniques & Types

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms. Almost all machine learning algorithms are data dependent, and […].

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400 million Twitter accounts’ data is on Christmas sale

Dataconomy

400 million Twitter accounts are affected by a massive Twitter data breach according to a hacker. Twitter CEO Elon Musk has been urged in a post on a criminal data breach forum by a member who claims to have gotten the emails and phone numbers of 400 million Twitter users. With users flocking to the […].

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Top 38 Python Libraries for Data Science, Data Visualization & Machine Learning

KDnuggets

This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.

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Crafting Serverless ETL Pipeline Using AWS Glue and PySpark

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview ETL (Extract, Transform, and Load) is a very common technique in data engineering. It involves extracting the operational data from various sources, transforming it into a format suitable for business needs, and loading it into data storage systems. Traditionally, ETL processes are […].

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Best Data Visualization Projects of 2022

FlowingData

Every year, I pick my favorite data visualization projects, which tend to cover a wide range of purposes but are typically for presentation. Here are my favorites for 2022. Read More.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Shield your organization’s data with Backup as a Service (BaaS)

Dataconomy

“As a Service” models, such as Backup as a Service (BaaS), Software as a Service (SaaS), Infrastructure as a Service (IaaS) have become increasingly important in recent years, as more and more organizations look to take advantage of the benefits of cloud computing. One of the main benefits of “as a service” models is the […].

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Key Data Science, Machine Learning, AI and Analytics Developments of 2022

KDnuggets

It's the end of the year, and so it's time for KDnuggets to assemble a team of experts and get to the bottom of what the most important data science, machine learning, AI and analytics developments of 2022 were.

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Top 10 blogs on NLP in Analytics Vidhya 2022

Analytics Vidhya

Introduction Natural language processing (NLP) is a field of computer science and artificial intelligence that focuses on the interaction between computers and human (natural) languages. It involves developing algorithms and models to analyze, understand, and generate human language, enabling computers to perform sentiment analysis, language translation, text summarization, and tasks.

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How to Plan a Cybersecurity Strategy for Your Small Business

Smart Data Collective

Do you think a small business owner need not worry about cyberattacks? 46% of all cyberattacks impact businesses with less than 1000 employees. Small businesses have fewer resources to invest in the security paradigm. That’s why; hackers find it easy to attack such vulnerable systems instead of large corporations who have spent millions of dollars on cybersecurity.

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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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Who will be the new CEO of Twitter? A friend of Musk or a famous leader…

Dataconomy

Who will be the new CEO of Twitter if Elon Musk takes the step-down poll seriously? In the poll, more than 10 million Twitter users expressed their desire for him to resign as Twitter CEO. Consequently, new Twitter CEO rumors immediately started. Mr.Beast, Jack Dorsey, and more… Several of the potential candidates have made their intentions clear, and others are the usual suspects for a position of this prominence.

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Data-Driven Holiday Cheer: How Santa is Using Analytics to Make the Season Bright

KDnuggets

Want to know how Santa might use data science to make his job easier? So did we, so we asked ChatGPT. Read on to find out what it said.

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Analytics Vidhya’s Top 10 Machine Learning Blogs in 2022

Analytics Vidhya

Introduction Though machine learning isn’t a relatively new concept, organizations are increasingly switching to big data and ML models to unleash hidden insights from data, scale their operations better, and predict and confront any underlying business challenges. All this positively impacts the ML industry while opening up new career avenues, job roles, a plethora of […].

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7 Ways to Avoid Errors In Your Data Pipeline

Smart Data Collective

A data pipeline is a technical system that automates the flow of data from one source to another. While it has many benefits, an error in the pipeline can cause serious disruptions to your business. Thankfully, there are ways to prevent them and avoid this company wide disruption. Here are some of the best practices for preventing errors in your data pipeline: 1.

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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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AI wars: Ukraine-based Reface app rivals Russian-based Lensa AI

Dataconomy

Reface app is the latest AI trend with its face swap and AI avatar features. So what’s the reason for this hype? While there are a lot of helpful usages of artificial intelligence in everyday life, one crucial factor sets it apart: entertainment value. After QQ Different Dimension Me, MyHeritage AI Time Machine, and Lensa […].

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The Zen of Python

KDnuggets

Python is one of the programming languages that are very versatile and relatively easy to learn. Hence it is the choice of many new programmers, regardless of what area of tech they are interested in. It is particularly popular in all data science branches.

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Top 5 Tips for Choosing the Right Database for Your Project

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Source: [link] As a developer, choosing the right database for your project is a crucial decision that can impact your project’s performance, scalability, and overall success. With so many available options, it can be overwhelming to determine which database best fits your […].

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2022: A productivity revolution

Cassie Kozyrkov

The year that changed the way we work Continue reading on The Startup »

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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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Dataconomy Wrapped 2022: The answers to your burning questions

Dataconomy

Do you remember all of your burning questions in 2022? We did that and gathered the top 10 questions you’ve been asking us about in Dataconomy Wrapped 2022. There were numerous additions to our regular routines this year and another year has come to a close. If there is one thing that has stood out […].

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5 Tasks To Automate With Python

KDnuggets

Here are 5 tasks you can automate with Python, and how to do it.

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Database Errors: Dark Side and Lessons Learned

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Source: Image by Pexels from Pixabay Have you ever wondered about the dark side of databases? We, software developers, rely on databases to store and manage important data for our applications. But as we all know, things can go wrong with databases […]. The post Database Errors: Dark Side and Lessons Learned appeared first on Analytics Vidhya.

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Niche Data Tactics to Take Your Business to the Next Level

Smart Data Collective

Big data can be an intimidating concept. Whether you’ve been using it for a while in your business or you’re just starting to explore the possibilities, there’s a lot to consider. Large corporations can hire dedicated data experts or even a full big data team , but small businesses have to be more selectively strategic in how they approach collecting and leveraging data.

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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Everything you need for school in one place: Caktus AI

Dataconomy

Caktus AI writer promises to free you from endless homework! Caktus AI is not here to compete with the big names of AI writers but to be the best buddy of educators everywhere. Caktus AI is a company that uses AI to rethink the classroom experience. According to the firm, artificial intelligence can help educators […].

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A Guide to Train an Image Classification Model Using Tensorflow

KDnuggets

Classify images at scale and with very high accuracy with the advent of machine learning and deep learning algorithms.

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Introduction to Apache Kafka: Fundamentals and Working

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Have you ever wondered how Instagram recommends similar kinds of reels while you are scrolling through your feed or ad recommendations for similar products that you were browsing on Amazon? All these sites use some event streaming tool to monitor user activities. […].

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Connecting Amazon Redshift and RStudio on Amazon SageMaker

AWS Machine Learning Blog

Last year, we announced the general availability of RStudio on Amazon SageMaker , the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale.

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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.