Data Science 101

SEPTEMBER 24, 2019

Open Source Data Science Projects. Is the list missing a project released in 2019? A number of new impactful open source projects have been released lately. If so, please leave a comment.

Data Science 104

Data Science Deep Learning Machine Learning Visualization 104

O'Reilly on Data

FEBRUARY 18, 2020

Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%. In 2019, as in 2018, Python was the most popular language on O’Reilly online learning.

Data-driven 339

Data-driven Software Statistics Marketing 339

Data Science 101

APRIL 29, 2019

Here is the latest data science news for the week of April 29, 2019. From Data Science 101. The Go Programming Language for Data Science Quick Video Tutorial for Find Updates in Azure Two-Minute Papers, One Pixel attack on NN. General Data Science. What do you think?

Data Science 81

Data Science Deep Learning Software Machine Learning 81

KDnuggets

DECEMBER 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.

Deep Learning 76

Deep Learning Machine Learning Data Science Technology 76

O'Reilly on Data

FEBRUARY 4, 2019

In this post, I’ll describe some of the key areas of interest and concern highlighted by respondents from Europe, while describing how some of these topics will be covered at the upcoming Strata Data conference in London (April 29 - May 2, 2019). Deep Learning. Temporal data and time-series.

Machine Learning 278

Machine Learning Enterprise IoT Big Data 278

KDnuggets

DECEMBER 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.

Deep Learning 79

Deep Learning Machine Learning Data Science Analytics 79

Dataiku

DECEMBER 16, 2019

What will be the hottest data science, machine learning, and AI trends in the new decade? Was 2019 really the year of NLP? Will we see more or less of deep learning and reinforcement learning in 2020?

Data Science 18

Data Science Reporting Deep Learning Machine Learning 18

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

Testing 312

Testing Machine Learning Consulting Data Quality 312

KDnuggets

SEPTEMBER 30, 2019

Also: 12 Deep Learning Researchers and Leaders; Natural Language in Python using spaCy: An Introduction; A Single Function to Streamline Image Classification with Keras; Which Data Science Skills are core and which are hot/emerging ones?; 6 bits of advice for Data Scientists.

Deep Learning 57

Deep Learning Data Science Analytics 57

KDnuggets

SEPTEMBER 17, 2019

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

Data Science 122

Data Science Deep Learning Statistics Machine Learning 122

Data Science 101

DECEMBER 2, 2019

AWS re:Invent 2019 starts today. It is a large learning conference dedicated to Amazon Web Services and Cloud Computing. Based upon the announcements last week , there will probably be a lot of focus around machine learning and deep learning.

Deep Learning 64

Deep Learning Machine Learning IT Data Science 64

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

KDnuggets

NOVEMBER 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.

Data Science 157

Data Science Technology Deep Learning Visualization 157

TDAN

JUNE 2, 2020

The domain of AI and data science so far has created significant value in the technological landscape. With multiple technologies involved, even deep learning algorithms can’t do the trick. 2019 witnessed record-breaking AI funding, and it’s mostly possible because, over the years, decision making has […].

Data Science 52

Data Science Deep Learning Technology Business Intelligence 52

KDnuggets

DECEMBER 11, 2019

AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments and Key Trends; Down with technical debt! Clean #Python for #DataScientists; Calculate Similarity?-?the the most relevant Metrics in a Nutshell.

Deep Learning 46

Deep Learning Machine Learning Data Science Metrics 46

Insight

SEPTEMBER 20, 2019

on test data. Discussion In this project, I used deep learning techniques to automatically detect lesion regions and classify the lesion, which can have both cost and time-saving benefits. Conclusions The deep learning model developed in this project can automatically detect lesions in the ultrasound images.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

KDnuggets

SEPTEMBER 4, 2019

This week: Object-oriented programming for data scientists; Deep Learning Next Step: Transformers and Attention Mechanism; R Users' Salaries from the 2019 Stackoverflow Survey; Types of Bias in Machine Learning; 4 Tips for Advanced Feature Engineering and Preprocessing; and much more!

Deep Learning 56

Deep Learning Data Science Machine Learning 56

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Scale the problem to handle complex data structures. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

CIO Business Intelligence

OCTOBER 4, 2023

We’ve been working on this for over a decade, including transformer-based deep learning,” says Shivananda. An example of the impact of AI can be seen from 2019 to 2022, when the company’s loss rate reduced by almost half, in part thanks to advances in algorithms and AI technology.

Digital Transformation 132

Digital Transformation Deep Learning Data Lake Risk 132

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

A more general approach is to learn a Generalized Additive Model (GAM). GAMs are popular among data science and machine learning applications for their simplicity and interpretability. Monotonic Deep Lattice Networks Deep learning is a powerful tool when we have an abundance of data to learn from.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

KDnuggets

DECEMBER 16, 2019

Also: Plotnine: Python Alternative to ggplot2; AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020; Moving Predictive Maintenance from Theory to Practice; 10 Free Top Notch Machine Learning Courses; Math for Programmers!

Machine Learning 46

Machine Learning Data Science Deep Learning Technology 46

O'Reilly on Data

DECEMBER 12, 2019

More structured approaches to sensitivity analysis include: Adversarial example searches : this entails systematically searching for rows of data that evoke strange or striking responses from an ML model. Figure 1 illustrates an example adversarial search for an example credit default ML model.

Machine Learning 194

Machine Learning Modeling Testing Risk Management 194

KDnuggets

JULY 30, 2019

Data Scientists need computing power. Whether you’re processing a big dataset with Pandas or running some computation on a massive matrix with Numpy, you’ll need a powerful machine to get the job done in a reasonable amount of time.

Data Science 97

Data Science Deep Learning Big Data 97

KDnuggets

DECEMBER 26, 2019

Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

Machine Learning 150

Machine Learning Data Science Deep Learning 150

O'Reilly on Data

MARCH 20, 2019

Watermarking is a term borrowed from the deep learning security literature that often refers to putting special pixels into an image to trigger a desired outcome from your model. It seems entirely possible to do the same with customer or transactional data. Security Attacks: Analysis of Machine Learning Models.”

Modeling 224

Modeling Machine Learning Predictive Modeling Consulting 224

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Machine learning model interpretability. back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

KDnuggets

AUGUST 7, 2019

This week on KDnuggets: What 70% of Data Science Learners Do Wrong; Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree; How a simple mix of object-oriented programming can sharpen your deep learning prototype; Can we trust AutoML to go on full autopilot?;

Data Science 47

Data Science Deep Learning Machine Learning 47

KDnuggets

AUGUST 12, 2019

Also: Deep Learning for NLP: ANNs, RNNs and LSTMs explained!; Machine Learning is Happening Now: A Survey of Organizational Adoption, Implementation, and Investment; 25 Tricks for Pandas; Getting Started with Data Science; Data Science: Scientific Discipline or Business Process?

Machine Learning 50

Machine Learning Data Science Deep Learning IT 50

KDnuggets

DECEMBER 11, 2019

We asked top experts: What were the main developments in AI, Data Science, Deep Learning, and Machine Learning Research in 2019, and what key trends do you expect in 2020?

Machine Learning 45

Machine Learning Deep Learning Data Science Analytics 45

KDnuggets

SEPTEMBER 2, 2019

Also: Types of Bias in Machine Learning; Deep Learning Next Step: Transformers and Attention Mechanism; New Poll: Data Science Skills; R Users Salaries from the 2019 Stackoverflow Survey; How to Sell Your Boss on the Need for Data Analytics.

Deep Learning 45

Deep Learning Machine Learning Visualization Data Science 45

CIO Business Intelligence

APRIL 15, 2022

Since the COVID-19 pandemic began, numerous organizations have sought to apply machine learning (ML) algorithms to help hospitals diagnose or triage patients faster. But according to the UK’s Turing Institute, a national center for data science and AI, the predictive tools made little to no difference.

Analytics 145

Analytics Machine Learning Insurance Testing 145

KDnuggets

DECEMBER 9, 2019

Also: Data Science Curriculum Roadmap; Enabling the Deep Learning Revolution; The Essential Toolbox for Data Cleaning; A Non-Technical Reading List for Data Science; The Future of Careers in Data Science & Analysis.

Deep Learning 59

Deep Learning Machine Learning Data Science 59

Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. Tools to Help Your Data Science Projects Excel.

Data Science 71

Data Science Machine Learning Big Data Interactive 71

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Pandas is a Python data science library that is constantly improving. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Reporting Data mining 98

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Cloudera

OCTOBER 1, 2022

It is pretty impressive just how much has changed in the enterprise machine learning and AI landscape. Thinking back to the conversations I had in late 2019, early 2020, most of the mainstream organizations I was talking to, meaning not the Facebooks and the Googles of the world, had very similar machine learning and AI journeys.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

KDnuggets

NOVEMBER 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.

Data Science 51

Data Science Reporting Deep Learning 51