- Data Scientists Have Developed a Faster Way to Reduce Pollution, Cut Greenhouse Gas Emissions - Jul 3, 2020.
Data science is helping with one of the world's most pressing issues. Read about an approach and specific steps being taken by data scientists to quickly reduce pollution and greenhouse gas emissions.
- Data Cleaning: The secret ingredient to the success of any Data Science Project - Jul 1, 2020.
With an uncleaned dataset, no matter what type of algorithm you try, you will never get accurate results. That is why data scientists spend a considerable amount of time on data cleaning.
- Software engineering fundamentals for Data Scientists - Jun 30, 2020.
As a data scientist writing code for your models, it's quite possible that your work will make its way into a production environment to be used by the masses. But, writing code that is deployed as software is much different than writing code for exploratory data analysis. Learn about the key approaches for making your code production-ready that will save you time and future headaches.
- Learn Data Science from Top Universities for Free - Jun 29, 2020.
Where to find free lectures, seminars and complete courses from the likes of MIT, Stanford and Harvard.
- How Much Math do you need in Data Science? - Jun 26, 2020.
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.
- Exploring the Real World of Data Science - Jun 26, 2020.
An article highlighting things I’ve learned in the real world about data science.
- KDnuggets™ News 20:n25, Jun 24: PyTorch Fundamentals You Should Know; Free Math Courses to Boost Your Data Science Skills - Jun 24, 2020.
A Classification Project in Machine Learning: a gentle step-by-step guide; Crop Disease Detection Using Machine Learning and Computer Vision; Bias in AI: A Primer; Machine Learning in Dask; How to Deal with Missing Values in Your Dataset
- KDnuggets™ News 20:n24, Jun 17: Easy Speech-to-Text with Python; Data Distributions Overview; Java for Data Scientists - Jun 17, 2020.
Also: Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container; Five Cognitive Biases In Data Science (And how to avoid them); Understanding Machine Learning: The Free eBook; Simplified Mixed Feature Type Preprocessing in Scikit-Learn with Pipelines; A Complete guide to Google Colab for Deep Learning
- Five Cognitive Biases In Data Science (And how to avoid them) - Jun 12, 2020.
Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work. Learn more about five biases that can all too easily make your seemingly objective work become surprisingly subjective.
- Top 6 Reasons Data Scientists Should Know Java - Jun 12, 2020.
There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.
- Fighting Disease with Data: Q&A with Epidemiologist Amrish Baidjoe - Jun 11, 2020.
Data science tools are powerful for investigating the current pandemic and other outbreaks, when accurate and actionable data are crucial. Epidemiologist and R Epidemics Consortium leader Amrish Baidjoe shared his insights into using data science to fight disease, from modeling to automation to new technologies.
- 3 Key Data Science Questions to Ask Your Big Data - Jun 3, 2020.
The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.
- Don’t Democratize Data Science - Jun 2, 2020.
A plethora of online courses and tools promise to democratize the field, but just learning a few basic skills does not a true data scientist make.
- Introduction to Pandas for Data Science - Jun 1, 2020.
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.
- KDD-2020 – Virtual Only Conference, Aug 23-27 - May 29, 2020.
After much consideration, the General Chairs, Executive Committee and Organizing Committee for KDD 2020 have decided to take the conference fully virtual. Clear your calendar for August 23-27, 2020, and enjoy access to all the virtual content live and on demand the week of the event.
- Best GIS Courses in 2020 - May 27, 2020.
Geographic Information Systems Analysis is the analysis of spatial relationships and patterns. Spatial components are being ingrained into society with the advent of the Internet of Things (IoT) in which more data can be connected and is likely to have a spatio-temporal component as well.
- Appropriately Handling Missing Values for Statistical Modelling and Prediction - May 22, 2020.
Many statisticians in industry agree that blindly imputing the missing values in your dataset is a dangerous move and should be avoided without first understanding why the data is missing in the first place.
- Complex logic at breakneck speed: Try Julia for data science - May 20, 2020.
We show a comparative performance benchmarking of Julia with an equivalent Python code to show why Julia is great for data science and machine learning.
- Analytic Professionals – Share your views: Participate in the 2020 Data Science Survey - May 12, 2020.
Analytics & data science professionals: take part now in the Rexer Analytics 2020 Data Science Survey and share your views.
- Data Scientists, Corporate Fortune Tellers - May 8, 2020.
I realized that from a corporate perspective, “fortune teller” was not entirely off from the role of a “data scientist”.
- Top 10 Data Visualization Tools for Every Data Scientist - May 5, 2020.
At present, the data scientist is one of the most sought after professions. That’s one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.
- How use the Coronavirus crisis to kickstart your Data Science career - May 4, 2020.
As the global economy dwindles, tech companies are hiring en masse. Now is the time to get yourself noticed as a Data Scientist and try to land your dream job.
- Outbreak Analytics: Data Science Strategies for a Novel Problem - Apr 30, 2020.
You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?
- Exploring the Impact of Geographic Information Systems - Apr 30, 2020.
GIS has mostly been behind more popular buzzwords like machine learning and deep learning. GIS has always been around us in the background being used in government, business, medicine, real estate, transport, manufacturing etc.
- Five Cool Python Libraries for Data Science - Apr 30, 2020.
Check out these 5 cool Python libraries that the author has come across during an NLP project, and which have made their life easier.
- KDnuggets™ News 20:n17, Apr 29: The Super Duper NLP Repo; Free Machine Learning & Data Science Books & Courses for Quarantine - Apr 29, 2020.
Also: Should Data Scientists Model COVID19 and other Biological Events; Learning during a crisis (Data Science 90-day learning challenge); Data Transformation: Standardization vs Normalization; DBSCAN Clustering Algorithm in Machine Learning; Find Your Perfect Fit: A Quick Guide for Job Roles in the Data World
- How Data Scientists Can Train and Updates Models to Prepare for COVID-19 Recovery - Apr 28, 2020.
The COVID-19 pandemic has affected everything, and building predictions during this time is difficult. Data science teams need to update their models to prepare for the recovery, and know how to properly train 2020 data models to learn from the coronavirus anomaly.
- Learning during a crisis (Data Science 90-day learning challenge) - Apr 24, 2020.
How can you keep your focus and drive during a global crisis? Take on a 90-day learning challenge for data science and check out this list of books and courses to follow.
- Should Data Scientists Model COVID19 and other Biological Events - Apr 22, 2020.
Biostatisticians use statistical techniques that your current everyday data scientists have probably never heard of. This is a great example where lack of domain knowledge exposes you as someone that does not know what they are doing and are merely hopping on a trend.
- Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition - Apr 22, 2020.
If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.
- Fast Track Your Data Science Career - Apr 21, 2020.
Earn a Master of Professional Studies in Data Analytics online through Penn State World Campus – and you can add in-demand skills to your wheelhouse while you continue to work.
- Dockerize Jupyter with the Visual Debugger - Apr 17, 2020.
A step by step guide to enable and use visual debugging in Jupyter in a docker container.
- Can Java Be Used for Machine Learning and Data Science? - Apr 14, 2020.
While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.
- Free Workshop Preview: Data Thinking with Martin Szugat - Apr 13, 2020.
As anticipation grows for Predictive Analytics World’s virtual conferences (PAW for Industry 4.0, PAW for Healthcare and Deep Learning World on 11-12 May 2020) and virtual workshops (13 May 2020), here is a chance to start familiarising yourself with the quality of the content and of the virtual networking. Gain an insight into how to apply design thinking for data science & analytics. Reserve your spot.
- Peer Reviewing Data Science Projects - Apr 13, 2020.
In any technical development field, having other practitioners review your work before shipping code off to production is a valuable support tool to make sure your work is error-proof. Even through your preparation for the review, improvements might be discovered and then other issues that escaped your awareness can be spotted by outsiders. This peer scrutiny can also be applied to Data Science, and this article outlines a process that you can experiment with in your team.
- KNIME Spring Summit Online Edition - Apr 10, 2020.
The KNIME Summits, in spring and fall, have been taking place since 2008 in Europe and the US. In light of the coronavirus, this year’s KNIME Spring Summit moved online. Not too late to participate: KNIME Spring Summit continues online. Check out the extended summit program now.
- Has AI Come Full Circle? A data science journey, or why I accepted a data science job - Apr 10, 2020.
Personal journeys in Data Science can vary greatly between individuals. Some are just getting starting and wading into this vast ocean of opportunity, and others have been involved during its decades-long evolution as a professional field. This review of a longer journey can provide a broader perspective of how you might fit into this interesting career.
- How Data Science Is Being Used to Understand COVID-19 - Apr 10, 2020.
Read this overview to gain an understanding of how data scientists are working hard to learn as much about COVID-19 as they can.
- 3 Best Sites to Find Datasets for your Data Science Projects - Apr 9, 2020.
When first learning data science, you will inevitably find yourself looking for more datasets to practice with. Here, we recommend the 3 best sites to find datasets to spark your next data science project.
- KDnuggets™ News 20:n14, Apr 8: Free Mathematics for Machine Learning eBook; Epidemiology Courses for Data Scientists - Apr 8, 2020.
Stop Hurting Your Pandas!; Python for data analysis... is it really that simple?!?; Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs; Build an app to generate photorealistic faces using TensorFlow and Streamlit; 5 Ways Data Scientists Can Help Respond to COVID-19 and 5 Actions to Avoid
- A Layman’s Guide to Data Science. Part 2: How to Build a Data Project - Apr 2, 2020.
As Part 2 in a Guide to Data Science, we outline the steps to build your first Data Science project, including how to ask good questions to understand the data first, how to prepare the data, how to develop an MVP, reiterate to build a good product, and, finally, present your project.
- Why you should NOT use MS MARCO to evaluate semantic search - Apr 2, 2020.
If we want to investigate the power and limitations of semantic vectors (pre-trained or not), we should ideally prioritize datasets that are less biased towards term-matching signals. This piece shows that the MS MARCO dataset is more biased towards those signals than we expected and that the same issues are likely present in many other datasets due to similar data collection designs.
- Advice for a Successful Data Science Career - Mar 30, 2020.
This blog is meant to show that most everyone has had to expend quite a bit of effort to get where they are. They have to work hard, sometimes experience failure, show discipline, be persistent, be dedicated to their goals, and sometimes sacrifice or take risks.
- SIGKDD Community Impact Program (Deadline Jun. 15) - Mar 27, 2020.
SIGKDD is announcing a funding opportunity through its Community Impact Program.The goal of the program is to support projects that promote data science and help the data science community to grow, broaden, and diversify. Read more here.
- Making sense of ensemble learning techniques - Mar 26, 2020.
This article breaks down ensemble learning and how it can be used for problem solving.
- Diffusion Map for Manifold Learning, Theory and Implementation - Mar 25, 2020.
This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.
- Improving the partnership between Data Science and IT - Mar 18, 2020.
Friction can quickly arise as a result of these separate workflows and priorities. Given their differences, how can data science and IT more seamlessly work together in building a model-driven organization?
- Scaling Your Data Strategy - Mar 17, 2020.
This article presents a particular vision for a cohesive data strategy for addressing large-scale problems with data-driven solutions, based on prior professional experiences.
- Covid-19, your community, and you — a data science perspective - Mar 11, 2020.
Let's talk about covid-19; the reality, the numbers, and the data science.
- The Berlin Rent Freeze: How many illegal overpriced offers can I find online? - Mar 10, 2020.
This post presents an analysis of Berlin online real estate listings, investigating a controversial law capping rents in the state, which went into effect on February 23. Are current landlords already respecting the new rent cap?
- 50 Must-Read Free Books For Every Data Scientist in 2020 - Mar 9, 2020.
In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.
- Resources for Women in AI, Data Science, and Machine Learning - Mar 8, 2020.
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
- How do we Better Solve Analytics Problems? - Mar 4, 2020.
Problem definition and solution development are key ingredients of being a consultant. Structuring the problem definition phase is critical to project success but may seem like a creative process.
- The Augmented Scientist Part 1: Practical Application Machine Learning in Classification of SEM Images - Mar 3, 2020.
Our goal here is to see if we can build a classifier that can identify patterns in Scanning Electron Microscope (SEM) images, and compare the performance of our classifier to the current state-of-the-art.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 2, 2020.
We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.
- Data Science Curriculum for self-study - Feb 26, 2020.
Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.
- Python and R Courses for Data Science - Feb 26, 2020.
Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.
- Probability Distributions in Data Science - Feb 26, 2020.
Some machine learning models are designed to work best under some distribution assumptions. Therefore, knowing with which distributions we are working with can help us to identify which models are best to use.
- KDnuggets™ News 20:n08, Feb 26: Gartner 2020 Magic Quadrant for Data Science & Machine Learning Platforms; Will AutoML Replace Data Scientists? - Feb 26, 2020.
This week in KDnuggets: The Death of Data Scientists - will AutoML replace them?; Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms; Hand labeling is the past. The future is #NoLabel AI; The Forgotten Algorithm; Getting Started with R Programming; and much, much more.
- Learning from 3 big Data Science career mistakes - Feb 25, 2020.
Thinking of data science as merely a technical profession, like programming, may take you away from your goals. We explain big mistakes to avoid, including not understanding the 2 cultures of statistics, and not understanding the shift to industrial focus.
- Free Mathematics Courses for Data Science & Machine Learning - Feb 25, 2020.
It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.
- 7 Data Trends for 2020 (and one non-trend) - Feb 24, 2020.
This article discusses trends that will (and won't) take shape in 2020.
- Data Science Influencers and Keynotes Coming to ODSC East 2020 - Feb 20, 2020.
ODSC is proud to announce its keynote speakers for ODSC East 2020, Apr 13-17 in Boston — ten preeminent researchers and visionaries who will kick off the already expert lineup set to speak at the community-based event for data science practitioners and AI engineers.
- Getting Started with R Programming - Feb 19, 2020.
An end to end Data Analysis using R, the second most requested programming language in Data Science.
- KDnuggets™ News 20:n07, Feb 19: 20 AI, Data Science, Machine Learning Terms for 2020; Why Did I Reject a Data Scientist Job? - Feb 19, 2020.
This week on KDnuggets: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020; Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist; Math for Programmers; Deep Neural Networks; Practical Hyperparameter Optimization; and much more!
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1) - Feb 18, 2020.
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.
- Seize Your New Career in Data Science - Feb 17, 2020.
Springboard’s mission has always been to enable everyone to attain their full potential by preparing students for the ever-changing world around them You can start working towards your dream data science career and land a new role by the end of summer.
- Fourier Transformation for a Data Scientist - Feb 14, 2020.
The article contains a brief intro into Fourier transformation mathematically and its applications in AI.
- Fidelity on How to Find a Tailor-Fit Unicorn Data Scientist - Feb 11, 2020.
Predictive Analytics World for Financial Services in Las Vegas, May 31-Jun 4 is honored to host an exceptional keynote by Fidelity Investments’ AI and Data Science Center of Excellence Leader, Victor Lo: "How to Find a Tailor-Fit 'Unicorn' Data Scientist for Financial Services". Use the code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket.
- The Data Science Puzzle — 2020 Edition - Feb 7, 2020.
The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.
- Top 5 Data Science Trends for 2020 - Feb 4, 2020.
As Data Science continues to expand into the next decade, this article features five important trends in the field that are expected in 2020. Leverage these trends to help improve your business processes for maximizing growth.
- Data Validation for Machine Learning - Jan 31, 2020.
While the validation process cannot directly find what is wrong, the process can show us sometimes that there is a problem with the stability of the model.
- Top 25 Session Highlights at ODSC East 2020 - Jan 29, 2020.
ODSC East is back in Boston, Apr 13-17, 2020. Preliminary schedule is a unique collection of the leading experts and rising stars of data science. Register soon, as our 50% discount ends this Friday, Jan 31!
- Google Dataset Search Provides Access to 25 Million Datasets - Jan 29, 2020.
Google's dataset search is out of beta, and provides centralized access to 25 million datasets.
- KDnuggets™ News 20:n04, Jan 29: AutoML: If you try it, you’ll like it more; The Data Science Interview Study Guide - Jan 29, 2020.
AutoML Poll results: if you try it, you'll like it more; The Data Science Interview Study Guide; What Do Data Scientists in Europe Do & How Much Are They Worth?; 2 Questions for a Junior Data Scientist
- Data Scientist Archetypes - Jan 28, 2020.
My goal here is to give you a map for navigating the sprawling terrain of data science. It’s to help you prioritize what you want to learn and what you want to do, so you don’t feel lost.
- The Decade of Data Science - Jan 27, 2020.
With the last decade being so strong for the emerging field of Data Science, this review considers current trends in the industry, popular frameworks, helpful tools, and new tools that can be leveraged more in the future.
- You’re Fired: How to develop and manage a happy data science team - Jan 27, 2020.
I want to share a solution called Insight-Driven Development (IDD), a few examples of it, and five steps to adopting it. IDD aims to create a high performing, engaged, and happy Data Science teams that embrace non-ML work as much as the fun ML stuff.
- What Do Data Scientists in Europe Do & How Much Are They Worth? - Jan 23, 2020.
Interested in knowing what a data scientist is worth in Europe, and what one does? Read this overview of a recent survey on the topic and gain some insight into the European data science professional job market.
- The Data Science Interview Study Guide - Jan 22, 2020.
Preparing for a job interview can be a full-time job, and Data Science interviews are no different. Here are 121 resources that can help you study and quiz your way to landing your dream data science job.
- Top 9 Mobile Apps for Learning and Practicing Data Science - Jan 17, 2020.
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.
- Handling Trees in Data Science Algorithmic Interview - Jan 16, 2020.
This post is about fast-tracking the study and explanation of tree concepts for the data scientists so that you breeze through the next time you get asked these in an interview.
- KDnuggets™ News 20:n02, Jan 15: Top 5 Must-have Data Science Skills; Learn Machine Learning with THIS Book - Jan 15, 2020.
This week: learn the 5 must-have data science skills for the new year; find out which book is THE book to get started learning machine learning; pick up some Python tips and tricks; learn SQL, but learn it the hard way; and find an introductory guide to learning common NLP techniques.
- Graph Machine Learning Meets UX: An uncharted love affair - Jan 13, 2020.
When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.
- 7 Steps to a Job-winning Data Science Resume - Jan 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.
- Fast Track Your Data Science Career - Jan 9, 2020.
Earn a Master of Professional Studies in Data Analytics online through Penn State World Campus – and you can add in-demand skills to your wheelhouse while you continue to work.
- 5 Hands-on Skills Every Data Scientist Needs in 2020 – Coming to ODSC East - Jan 7, 2020.
Here are our top five hands-on training focus areas that every data scientist should know and that we’re paying extra attention to at ODSC East 2020 this April 13-17 in Boston.
- 7 Resources to Becoming a Data Engineer - Jan 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.
- Why Python is One of the Most Preferred Languages for Data Science? - Jan 3, 2020.
Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks.
- How HR Is Using Data Science and Analytics to Close the Gender Gap - Jan 3, 2020.
The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.
- What is the most important question for Data Science (and Digital Transformation) - Dec 31, 2019.
With so many buzzwords surrounding AI and machine learning, understanding which can bring business value and which are best left in the lab to mature is difficult. While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.
- How To “Ultralearn” Data Science: summary, for those in a hurry - Dec 30, 2019.
For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.
- How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4 - Dec 27, 2019.
In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.
- What is a Data Scientist Worth? - Dec 23, 2019.
What is the Salary of a Data Scientist in 2019? Let's have a look at some data to see how we can answer that question.
- How To “Ultralearn” Data Science: optimization learning, Part 3 - Dec 20, 2019.
This third part in a series about how to "ultralearn" data science will guide you through how to optimize your learning through five valuable techniques.
- The Most In Demand Tech Skills for Data Scientists - Dec 20, 2019.
By the end of this article you’ll know which technologies are becoming more popular with employers and which are becoming less popular.
- Alternative Cloud Hosted Data Science Environments - Dec 19, 2019.
Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.
- How To “Ultralearn” Data Science: removing distractions and finding focus, Part 2 - Dec 17, 2019.
This second part in a series about how to "ultralearn" data science will guide you through several techniques to remove those distractions -- because your focus needs more focus.
- How To “Ultralearn” Data Science, Part 1 - Dec 13, 2019.
What is "ultralearning" and how can you follow the strategy to become an expert of data science? Start with this first part in a series that will guide you through this self-motivated methodology to help you efficiently master difficult skills.
- Plotnine: Python Alternative to ggplot2 - Dec 12, 2019.
Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020 - Dec 11, 2019.
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.
- The 4 Hottest Trends in Data Science for 2020 - Dec 9, 2019.
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
- The Rise of User-Generated Data Labeling - Dec 4, 2019.
Let’s say your project is humongous and needs data labeling to be done continuously - while you’re on-the-go, sleeping, or eating. I’m sure you’d appreciate User-generated Data Labeling. I’ve got 6 interesting examples to help you understand this, let’s dive right in!
- KDnuggets™ News 19:n46, Dec 4: The Future of Data Science Careers; Which Data Visualization Should I Use? - Dec 4, 2019.
This week: The Future of Careers in Data Science & Analysis; Task-based effectiveness of basic visualizations; Open Source Projects by Google, Uber and Facebook for Data Science and AI; Getting Started with Automated Text Summarization; A Non-Technical Reading List for Data Science; and much more!
- Data Science Curriculum Roadmap - Dec 3, 2019.
What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.
- A Non-Technical Reading List for Data Science - Dec 2, 2019.
The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.
- Top 7 Data Science Use Cases in Trust and Security - Dec 2, 2019.
What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.
- Open Source Projects by Google, Uber and Facebook for Data Science and AI - Nov 28, 2019.
Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
- Cartoon: Thanksgiving, Big Data, and Turkey Data Science… - Nov 28, 2019.
A classic KDnuggets Thanksgiving cartoon examines the predicament of one group of fowl Data Scientists.
- The Future of Careers in Data Science & Analysis - Nov 27, 2019.
As the fields of data science and analysis continue to expand, the next crop of bright minds is always needed. Learn more about the nuances of these jobs and find where you can fit in for a rewarding and interesting career.
- Would you buy insights from this guy? (How to assess and manage a Data Science vendor) - Nov 25, 2019.
With all the hype from data science vendors selling "actionable insights" to boost your company's bottom line, selecting your analytics partner should proceed through the same, careful process as any traditional business endeavor. Follow these questions and best practices to ensure you manage accordingly.
- Top 8 Data Science Use Cases in Marketing - Nov 25, 2019.
In this article, we want to highlight some key data science use cases in marketing. Let us concentrate on several instances that present particular interest and managed to prove their efficiency in the course of time.
- Reproducibility, Replicability, and Data Science - Nov 19, 2019.
As cornerstones of scientific processes, reproducibility and replicability ensure results can be verified and trusted. These two concepts are also crucial in data science, and as a data scientist, you must follow the same rigor and standards in your projects.
- Data Science for Managers: Programming Languages - Nov 19, 2019.
In this article, we are going to talk about popular languages for Data Science and briefly describe each of them.
- KDnuggets™ News 19:n43, Nov 13: Dynamic Reports in Python and R; Creating NLP Vocabularies; What is Data Science? - Nov 13, 2019.
On KDnuggets this week: Orchestrating Dynamic Reports in Python and R with Rmd Files; How to Create a Vocabulary for NLP Tasks in Python; What is Data Science?; The Complete Data Science LinkedIn Profile Guide; Set Operations Applied to Pandas DataFrames; and much, much more.
- What is Data Science? - Nov 8, 2019.
Data Science is pitched as a modern and exciting job offering high satisfaction. Does its reality really live up to the hype? Here, we show what it's really like to work as a Data Scientist.
- Set Operations Applied to Pandas DataFrames - Nov 7, 2019.
In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.
- Data Sources 101 - Oct 28, 2019.
Data collection is one of the first steps of the data lifecycle — you need to get all the data you require in the first place. To collect the right data, you need to know where to find it and determine the effort involved in collecting it. This article answers the most basic question: where does all the data you need (or might need) come from?
- DataTech20 Seeking Speaker Submissions (16 March 2020, Glasgow) - Oct 28, 2019.
DataTech is a one-day conference on 16 Mar 2020, at the Technology and Innovation Centre in Glasgow, focusing on key topics in data science, and welcoming members of industry, academia, and the public sector alike. DataTech provides a forum for these different communities to meet, share knowledge and expertise, and forge new collaborations. We are currently welcoming workshop, talk and poster proposals for the DataTech20 conference.
- Bye Data Scientists, Hello AI? Not Likely! - Oct 22, 2019.
AI is becoming more mainstream. The fact that computers/robots will learn after being built and will surpass a human's intelligence is terrifying.
- How to Write Web Apps Using Simple Python for Data Scientists - Oct 22, 2019.
Convert your Data Science Projects into cool apps easily without knowing any web frameworks.
- How to Get the Most out of ODSC West 2019 - Oct 18, 2019.
ODSC West comes to San Francisco on Oct 29 - Nov 1. With over 300 hours of content, 200+ speakers, and thousands of attendees, there is certainly a lot to see, learn, and do at the conference. Register by Friday for 10% off your pass.
- KDnuggets™ News 19:n39, Oct 16: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI - Oct 16, 2019.
This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.
- Using DC/OS to Accelerate Data Science in the Enterprise - Oct 15, 2019.
Follow this step-by-step tutorial using Tensorflow to setup a DC/OS Data Science Engine as a PaaS for enabling distributed multi-node, multi-GPU model training.
- Top 7 Things I Learned in my Data Science Masters - Oct 15, 2019.
Even though I’m still in my studies, here’s a list of the most important things I’ve learned (as of yet).
- An ODSC West Guide to the Most Important Topics in Data Science Right Now - Oct 10, 2019.
In this article, we’ll outline just a few of the most important topics in data science that our speakers will be presenting on at ODSC West Oct 29 - Nov 1 in San Francisco.
- Data Science is Boring (Part 2) - Oct 9, 2019.
Why I love boring ML problems and how I think about them.
- The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization - Oct 7, 2019.
As a data scientist, your most important skill is creating meaningful visualizations to disseminate knowledge and impact your organization or client. These seven principals will guide you toward developing charts with clarity, as exemplified with data from a recent KDnuggets poll.
- The Last SQL Guide for Data Analysis You’ll Ever Need - Oct 4, 2019.
This is it: the last SQL guide for data analysis you'll ever need! OK, maybe it’s actually the first. But it’ll give you a solid head start.