Cracking KNIME!!

Laser 11 May 2022 08:56 LEARNING » e-learning - Tutorial

Cracking KNIME!!
Published 05/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 10 lectures (1h 35m) | Size: 958.8 MB

Basics of K
How to select different ML models for different Data sets
Building ML Models on multiple different kind of Data Sets
In a brief and systematic manner, evaluate, analyse, and convey the results of the ML models.

No Prerequisite required. Basic Excel is more than enough for you to start the course.

This is a course for Business Enthusiasts who look for data-driven decision-making techniques for different business scenarios. This would provide a basic and intermediate level understanding of different Machine Learning Algorithms and how they can be implemented in K. It would also teach the students how to judge the different Machine Learning Algorithms and which ones will fit your business scenario. K is free and powerful software that has a vast number of business use cases. K is used in many huge corporates and also in startups. This would also be ideal for any student who is pursuing an MBA with a major in Operations and Data Science.

K Analytics Platform is the open-source software for creating data science. Intuitive, open, and continuously integrating new developments, K makes understanding data and designing data science workflows and reusable components accessible to everyone. K is a great tool of choice for people with no programming background and looking for a free tool. K is a great tool for people not fully comfortable with python syntax. It is great for database manipulation and wrangling. It has a visual drag and drop interface and allows an amazing number of advanced data analytics. K Software allows you to reach back into the data science cycle at predeteed touchpoints to update data sources, tweak parameters, inject domain knowledge, and more - all this without touching an actual workflow.


Bners in K who would want to learn about different ML Models




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