FineReport

DECEMBER 19, 2019

At the same time, it also advocates visual exploratory analysis. The visualization component library of FineReport is very rich. Pandas incorporates a large number of analysis function methods, as well as common statistical models and visualization processing. It is recommended that everyone learn to learn.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

O'Reilly on Data

DECEMBER 12, 2019

If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. Figure 1 illustrates an example adversarial search for an example credit default ML model. The main drawback of residual analysis is that to calculate residuals, true outcomes are needed.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

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%. But sustained interest in cloud migrations—usage was up almost 10% in 2019, on top of 30% in 2018—gets at another important emerging trend. Still cloud-y, but with a possibility of migration.

Data-driven 335

Data-driven Software Statistics Marketing 335

datapine

NOVEMBER 19, 2019

Exciting and futuristic, the concept of computer vision is based on computing devices or programs gaining the ability to extract detailed information from visual images. While we’ve seen traces of this in 2019, it’s in 2020 that computer vision will make a significant mark in both the consumer and business world.

Technology 279

Technology Internet of Things IT IoT 279

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. 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

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 123

Data Science Deep Learning Statistics Machine Learning 123

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105