* Cantinho Satkeys

Refresh History
  • JPratas: try65hytr Pessoal  h7ft6l k7y8j0
    Hoje às 03:51
  • j.s.: try65hytr a todos  4tj97u<z
    30 de Outubro de 2024, 21:00
  • JPratas: dgtgtr Pessoal  4tj97u<z k7y8j0
    28 de Outubro de 2024, 17:35
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  k8h9m
    27 de Outubro de 2024, 11:21
  • j.s.: bom fim de semana   49E09B4F 49E09B4F
    26 de Outubro de 2024, 17:06
  • j.s.: dgtgtr a todos  4tj97u<z
    26 de Outubro de 2024, 17:06
  • FELISCUNHA: ghyt74   49E09B4F  e bom fim de semana
    26 de Outubro de 2024, 11:49
  • JPratas: try65hytr Pessoal  101yd91 k7y8j0
    25 de Outubro de 2024, 03:53
  • JPratas: dgtgtr A Todos  4tj97u<z 2dgh8i k7y8j0
    23 de Outubro de 2024, 16:31
  • FELISCUNHA: ghyt74  pessoal   49E09B4F
    23 de Outubro de 2024, 10:59
  • j.s.: dgtgtr a todos  4tj97u<z
    22 de Outubro de 2024, 18:16
  • j.s.: dgtgtr a todos  4tj97u<z
    20 de Outubro de 2024, 15:04
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  101041
    20 de Outubro de 2024, 11:37
  • axlpoa: hi
    19 de Outubro de 2024, 22:24
  • FELISCUNHA: ghyt74   49E09B4F  e bom fim de semana  4tj97u<z
    19 de Outubro de 2024, 11:31
  • j.s.: ghyt74 a todos  4tj97u<z
    18 de Outubro de 2024, 09:33
  • JPratas: try65hytr Pessoal  4tj97u<z classic k7y8j0
    18 de Outubro de 2024, 03:28
  • schmeagle: iheartradio
    17 de Outubro de 2024, 22:58
  • j.s.: dgtgtr a todos  4tj97u<z
    17 de Outubro de 2024, 18:09
  • FELISCUNHA: ghyt74  pessoal   49E09B4F
    17 de Outubro de 2024, 09:09

Autor Tópico: Logistic Regression, LDA and KNN in R for Predictive Modeling  (Lida 216 vezes)

0 Membros e 1 Visitante estão a ver este tópico.

Online mitsumi

  • Moderador Global
  • ***
  • Mensagens: 115351
  • Karma: +0/-0
Logistic Regression, LDA and KNN in R for Predictive Modeling
« em: 30 de Setembro de 2019, 18:15 »

Logistic Regression, LDA and KNN in R for Predictive Modeling
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 5 Hours | 2.52 GB
Genre: eLearning | Language: English

You're looking for a complete Classification modeling course that teaches you everything you need to create a Classification model in R, right? You've found the right Classification modeling course covering logistic regression, LDA and KNN in R studio!

The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course. Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

This course teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems. We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay if you learn how to run and interpret the result as taught in the practical lectures. We also look at how to quantify model's performance using confusion matrix, how categorical variables in the independent variables dataset are interpreted in the results, test-train split and how do we finally interpret the result to find out the answer to a business problem. By the end of this course, your confidence in creating a classification model in R will soar. You'll have a thorough understanding of how to use Classification modeling to create predictive models and solve business problems.

All the code and supporting files for this course are available at -
Só visivel para registados e com resposta ao tópico.

Only visible to registered and with a reply to the topic.
             

               

Download link:
Só visivel para registados e com resposta ao tópico.

Only visible to registered and with a reply to the topic.

Links are Interchangeable - No Password - Single Extraction