8.1 The Future of Machine Learning 8.1 The Future of Machine Learning Without machine learning there can be no interpretable machine learning. Therefore we have to guess where ...
10.6 Exercises References 10.6 Exercises Read the script 10-centroid-alg.R in the code folder of the book’s GitHub repo. Which of the best practices covered in Section 10.2...
Conclusion Conclusion Many thanks for reading this book. I hope you’ve found something of interest in its pages. If you did enjoy it please tell your friends about it. If you ...
2 Why Julia? 2 Why Julia? The world of data science is filled with different open source programming languages. Industry has, mostly, adopted Python and academia R. Why bother ...
Features Features This is a short demonstration textbook to show the general layout / style of textbooks builtwith Jupyter and Jekyll. To begin, click on one of the chapter se...
3.4 Filesystem 3.4 Filesystem In data science, most projects are undertaken in a collaborative effort. We share code, data, tables, figures and so on. Behind everything, there i...
Videos Keynote: Machine Learning using Kubeflow and Kubernetes Enabling Kubeflow with Enterprise-Grade Auth for On-Prem Deployments Supercharge Kubeflow Performance on GPU Cluste...
Videos Keynote: Machine Learning using Kubeflow and Kubernetes Enabling Kubeflow with Enterprise-Grade Auth for On-Prem Deployments Supercharge Kubeflow Performance on GPU Cluste...