Machine learning projects for beginners, final year students, and professionals. The list consists of guided projects, tutorials, and example source code.
Samples and Tools for Windows ML. Contribute to microsoft/Windows-Machine-Learning development by creating an account on GitHub.
Samples and Tools for Windows ML. Contribute to microsoft/Windows-Machine-Learning development by creating an account on GitHub.
dataset, sample, feature, feature value, feature space, feature vector(一个示例) 样本的维数(dimensionality), label, learning/training, multi-class classification, clustering, supervised learning + unsupervised learning. generalization 泛化能力,IID (Independent Identical Distribution). 归纳(induction)与演绎...
MachineLearningSample. Contribute to palanceli/MachineLearningSample development by creating an account on GitHub.
Machine learning projects are only as effective as the system and resources they’re built with. That highlights the need to invest in proper planning and preparation. The following are some of the most common challenges facing machine learning projects: Data quality: The adage “garbage in, gar...
It’s a must have tool for machine learning projects in R. For more information about the caret R package see the caret package homepage. 2. Load The Data We are going to use the iris flowers dataset. This dataset is famous because it is used as the “hello world” dataset in machine...
Machine Learning Project Checklist This checklist can guide you through your Machine Learning projects. There areeight main steps: Frame the problem and look at the big picture. Get the data. Explore the data to gain insights. Prepare the data to better expose the underlying data patterns to ...
Machine Learning Challenges Machine learning projects are only as effective as the system and resources they’re built with. That highlights the need to invest in proper planning and preparation. The following are some of the most common challenges facing machine learning projects: ...
This document attempts to develop a curated list of Machine Learning resources, including books, papers, software, libraries, notebooks, etc. Most of the libraries are for Python though the rest of the materials here are generally suited for working with data. ...