KDnuggets

JANUARY 9, 2020

This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.

Machine Learning 400

Machine Learning Machine Learning Algorithm 400

Analytics Vidhya

JANUARY 5, 2020

Introducing the Learning Path to become a Data Scientist in 2020! Learning paths are easily one of the most popular and in-demand resources we. The post Your Ultimate Learning Path to Become a Data Scientist and Machine Learning Expert in 2020 appeared first on Analytics Vidhya.

Data Scientist 400

Data Scientist Machine Learning Machine Learning Analytics 400

Dataconomy

JANUARY 9, 2020

From wild speculation that flying cars will become the norm to robots that will be able to tend to our every need, there is lots of buzz about how AI, Machine Learning, and Deep Learning will change our lives. However, at present, it seems like a far-fetched future. As we. The post 2020: The Decade of Intelligent, Democratized Data appeared first on Dataconomy.

Deep Learning 243

Deep Learning Deep Learning Machine Learning Machine Learning 243

DataRobot

JANUARY 10, 2020

Does your organization apply appropriate human resources governance when hiring staff? Large enterprises tend to follow the same basic processes for hiring human staff. First, hiring managers write a job description, including the tasks the position requires and the skills and attributes of a suitable candidate. Job vacancies are posted, sometimes recruiters are also used, and people submit their resumes for consideration.

Data Science 132

Data Science AI AI 132

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

Analytics

KDnuggets

JANUARY 8, 2020

The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.

Data Science 400

Data Science Data Scientist SQL Machine Learning 400

Analytics Vidhya

JANUARY 8, 2020

Introduction Google “NLP jobs” and a remarkable number of relevant searches show up. There are businesses spinning up around the world that cater exclusively. The post A Comprehensive Learning Path to Understand and Master NLP in 2020 appeared first on Analytics Vidhya.

Analytics 306

Analytics Analytics Natural Language Processing 306

Data Science 101

JANUARY 6, 2020

As 2020 begins, there has been limited cloud data science announcements so I put together some predictions. Here are 3 things I believe will happen in 2020. 1. Cloud Collaboration. I think we are going to see more interoperability between the major cloud providers. For example, Azure Arc now allows you to run Azure products on a kubernetes container running anywhere (even in Amazon Web Services or Google Cloud) and AWS Outposts runs AWS on-premise.

Data Science 116

Data Science Cloud Data Azure Data Scientist 116

KDnuggets

JANUARY 7, 2020

Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.

Natural Language Processing 400

Natural Language Processing 400

Analytics Vidhya

JANUARY 6, 2020

Introduction What a time to be working in the deep learning space! 2019 was chock full of deep learning-powered developments and breakthroughs – it. The post A Comprehensive Learning Path for Deep Learning in 2020 appeared first on Analytics Vidhya.

Deep Learning 271

Deep Learning Deep Learning Analytics Analytics 271

Eugene Yan

JANUARY 5, 2020

Building a baseline recsys based on data scraped off Amazon. Warning - Lots of charts! (Part 1 of 2).

100

100

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

AI

Machine Learning (Theory)

JANUARY 4, 2020

This blog has been quiet for the last year. I have quite a bit to write about but found myself often out of time between work at Microsoft, ICML duties, and family life. Nevertheless, I expect to get back to more substantive discussions as I adjust to the new load. In the meantime, I’ve updated the site in various ways: SSL now works, and mail for people registering new accounts should work again.

100

100

KDnuggets

JANUARY 7, 2020

An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.

Data Engineering 400

Data Engineering Data Engineer Data Engineering Data Engineering 400

Analytics Vidhya

JANUARY 8, 2020

Introduction There are an overwhelming number of resources out there these days to learn computer vision concepts. How do you pick and choose from. The post Here’s your Learning Path to Master Computer Vision in 2020 appeared first on Analytics Vidhya.

Analytics 251

Analytics Analytics Deep Learning Deep Learning 251

Data Science 101

JANUARY 8, 2020

What is Artificial Intelligence (AI)? Artificial Intelligence has nearly as many definitions as people you ask. Here are two intriguing definitions I have heard. “Anything Computers cannot do … yet!” appears in many places , original source unknown. This is actually a pretty good definition, but it is always changing so it is hard to evaluate and compare.

ML 96

ML ML Machine Learning Machine Learning 96

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

AI

DataRobot

JANUARY 9, 2020

It’s a new year and a new decade, so we’re tapping into the minds of some of our leading industry experts and general managers (GMs) to find out what big trends they see emerging in the coming months. Learn more about AI demand forecasting for retailers, spatial data for sports analytics, and much more.

AI 17

AI AI Analytics Analytics 17

KDnuggets

JANUARY 8, 2020

Check out this collection of 10 Python snippets that can be taken as a reference for your daily work.

Python 396

Python 396

Victor Zhou

JANUARY 10, 2020

Quick - what sport is depicted in this image? Image from the CloudCV VQA Demo You probably immediately knew the answer: baseball. Easy, right? Now imagine you’re a computer. You’re given that same image and the text ” what sport is depicted in this image? ” and asked to produce the answer. Not so easy anymore, is it? This problem is known as Visual Question Answering (VQA) : answering open-ended questions about images.

Python 52

Python Deep Learning Deep Learning Natural Language Processing 52

Data Science 101

JANUARY 7, 2020

Are you an organization new to data science? Trying to implement the latest methods in Artificial Intelligence might not be the best way to start. It is better to start with a plan. Identify where you are and where you want to be. I call this a data strategy. I just released a free Data Strategy Email Course. Hopefully, this will help get your organization off to a smoother start with data science and artificial intelligence.

Artificial Intelligence 83

Artificial Intelligence Artificial Intelligence Data Science 83

Speaker: Frank Taliano

Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.

AI

DataRobot

JANUARY 6, 2020

As a football fan who is also a data scientist, the one question I get asked the most by my friends is this:

Data Science 16

Data Science Data Scientist AI AI 16

KDnuggets

JANUARY 10, 2020

A resume plays a key role in bagging that dream data science job. We break down the nuances of a job-winning data science resume so that you can go ahead and transform your own resume.

Data Science 388

Data Science 388

DataCentric podcast

JANUARY 6, 2020

It's been an eventful year, but largely one setting chess pieces up for what's to come. Moor Insights & Strategy technology analysts Steve McDowell and Matt Kimball each give their top trends of the past year. Not to spoil it, but you can jump directly to the topics from the timeline below: 00:50 Silicon is Sexy Again! Whether we're talking about AMD, ARM, Ampere, NVIDIA, Intel, or one of the emerging players, we're talking about chips. 03:13 The Year of AI Enablement, both a

AI 52

AI AI 52

Data Science 101

JANUARY 10, 2020

2020 is now in full swing and the announcements are starting to show up. There are some good ones this week. News. Google Releases a tool for Automated Exploratory Data Analysis Exploring data is one of the first activities a data scientist performs after getting access to the data. This command-line tool helps to determine the properties and quality of the data as well the predictive power.

Data Science 78

Data Science Power BI Cloud Data Exploratory Data Analysis 78

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?

Shreyansh Singh

JANUARY 4, 2020

Get the challenge from here vm1.exe implements a simple 8-bit virtual machine (VM) to try and stop reverse engineers from retrieving the flag. The VM’s RAM contains the encrypted flag and some bytecode to decrypt it. Can you figure out how the VM works and write your own to decrypt the flag? A copy of the VM’s RAM has been provided in ram.bin (this data is identical to the ram content of the malware’s VM before execution and contains both the custom assembly code and encrypted flag).

Python 52

Python 52

KDnuggets

JANUARY 6, 2020

Reducing images to numbers makes them amenable to computation. Let's take a look at the why and the how using Python and Numpy.

Python 380

Python 380

KDnuggets

JANUARY 8, 2020

Simply put: This post is about installing SQL, explaining SQL and running SQL.

SQL 362

SQL 362

KDnuggets

JANUARY 4, 2020

Ethics in AI has received significant attention recently, and the new KDnuggets cartoon examines the problem of teaching ethics to artificially intelligent entities.

Artificial Intelligence 332

Artificial Intelligence Artificial Intelligence AI AI 332

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

KDnuggets

JANUARY 9, 2020

Data Scientists work with tons of data, and many times that data includes natural language text. This guide reviews 7 common techniques with code examples to introduce you the essentials of NLP, so you can begin performing analysis and building models from textual data.

Data Scientist 307

Data Scientist Data Preparation 307

KDnuggets

JANUARY 6, 2020

This article is an overview of H2O, a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks.

Machine Learning 300

Machine Learning Machine Learning Python 300

KDnuggets

JANUARY 9, 2020

Time series analysis will be the best tool for forecasting the trend or even future. The trend chart will provide adequate guidance for the investor. So let us understand this concept in great detail and use a machine learning technique to forecast stocks.

Machine Learning 296

Machine Learning Machine Learning 296

KDnuggets

JANUARY 10, 2020

Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently.

AI 291

AI AI 291

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!