Neural Networks are powerful but complex and opaque tools. Using Topological Data Analysis, we can describe the functioning and learning of a convolutional neural network in a compact and understandable way.
A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
We all know correlation doesn’t equal causality at this point, but when working with time series data, correlation can lead you to come to the wrong conclusion.
While KDnuggets takes no side, we present the informative and respectful back and forth as we believe it has value for our readers. We hope that you agree.
KDnuggets poll compares Machine Learning Engineer, Researcher, Data Scientist and other professions and identifies one with the highest job satisfaction. Job satisfaction usually starts high, but drops significantly after 4 years on the job.
We find 6 tools form the modern open source Data Science / Machine Learning ecosystem; examine whether Python declared victory over R; and review which tools are most associated with Deep Learning and Big Data.
A comprehensive list of resources for Women in Data Science and Machine Learning, including a list of useful tech groups and published lists for finding Women speakers.
Judea Pearl has made noteworthy contributions to artificial intelligence, Bayesian networks, and causal analysis. These achievements notwithstanding, Pearl holds some views many statisticians may find odd or exaggerated.
5 Data Science Projects That Will Get You Hired in 2018
The 6 components of Open-Source Data Science/ Machine Learning Ecosystem; Did Python declare victory over R?
| 