Udacity Machine Learning Nanodegree (MLND) Capstone Project Guidelines
See more in the series visit the main course outline page
Technical proposal highlighing the real world problem, research done so far, and your research and approach in the field. Identify the correct datasets. Use Kaggle or DevPost to identify a problem. Proposal has to match final project. Kaggle might have already defined some of the requirements. Basic datasets like the MNIST cannot be used. Can use a representative sample of a large dataset. In essence Kaggle is the fastest. Discuss each section of the proposal. Be as detailed as possible. The requirement is high. As always Rubric is the most important evaluation criteria. Provide all important supplement materials.
Saturday, March 2, 2019
Data visualization of common math formula.
This review is updated continuously throughout the program. Yay I just joined the Udacity Nanodegree for Digital Marketing! I am such an Uda...
All you need to know about Snap IPO. Tech startup news explained for Youtubers in minutes.
The bogus request from P2PU to hunt for HTML tags in real life has yielded a lot of good thoughts. My first impression was that this is stup...