|
[ FreeCourseWeb.com ] Data Science Foundations: Data Assessment for Predictive Modeling
Download More Latest Courses Visit -->> https://FreeCourseWeb.com
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + .srt | Duration: 4h 3m | Size: 855 MB
CRISP-DM, the cross-industry standard process for data mining, is composed of six phases. Most new data scientists rush to modeling because it's the phase in which they have the most training. But whether the project succeeds or fails is actually determined far earlier. This course introduces a systematic approach to the data understanding phase for predictive modeling. Instructor Keith McCormick teaches principles, guidelines, and tools, such as KNIME and R, to properly assess a data set for its suitability for machine learning. Discover how to collect data, describe data, explore data by running bivariate visualizations, and verify your data quality, as well as make the transition to the data preparation phase. The course includes case studies and best practices, as well as challenge and solution sets for enhanced knowledge retention. By the end, you should have the skills you need to pay proper attention to this vital phase of all successful data science projects.
Topics include:
Distinguishing data assessment from data viz
Mastering the four data understanding tasks
Collecting initial data
Identifying the level of measurement
Loading data
Describing data
Visualizing data
Working with top predictors
Using ggplot2 for data viz
Verifying data quality
Transitioning to data preparation
Use Winrar to Extract. And use a shorter path when extracting, such as C: drive
ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)
Download More Latest Courses Visit -->> https://FreeCourseWeb.com
Get Latest Apps Tips and Tricks -->> https://AppWikia.com
We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...
|
|
udp://opentor.org:2710/announce udp://p4p.arenabg.com:1337/announce udp://tracker.torrent.eu.org:451/announce udp://tracker.cyberia.is:6969/announce udp://9.rarbg.to:2710/announc udp://explodie.org:6969/announce udp://tracker.moeking.me:6969/announce udp://tracker.opentrackr.org:1337/announce udp://tracker.tiny-vps.com:6969/announce udp://ipv4.tracker.harry.lu:80/announce udp://tracker.coppersurfer.tk:6969/announce udp://tracker.leechers-paradise.org:6969/announce udp://open.stealth.si:80/announce udp://tracker.pirateparty.gr:6969/announce udp://inferno.demonoid.is:3391/announce |
