* Cantinho Satkeys

Refresh History
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  4tj97u<z
    03 de Novembro de 2024, 10:49
  • j.s.: bom fim de semana  43e5r6 49E09B4F
    02 de Novembro de 2024, 08:37
  • j.s.: ghyt74 a todos  4tj97u<z
    02 de Novembro de 2024, 08:36
  • FELISCUNHA: ghyt74   49E09B4F  e bom feriado   4tj97u<z
    01 de Novembro de 2024, 10:39
  • JPratas: try65hytr Pessoal  h7ft6l k7y8j0
    01 de Novembro de 2024, 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

Autor Tópico: Theoretical Machine Learning From Scratch - Linear Models  (Lida 114 vezes)

0 Membros e 1 Visitante estão a ver este tópico.

Online mitsumi

  • Moderador Global
  • ***
  • Mensagens: 115675
  • Karma: +0/-0
Theoretical Machine Learning From Scratch - Linear Models
« em: 19 de Abril de 2021, 15:06 »
MP4 | Video: h264, 1280x720 | Audio: AAC, 48000 Hz
Language: English | Size: 747 MB | Duration: 2h 5m

What you'll learn
Understand the math behind linear models particularly linear and logistic regression
Uncover the black box understand the inner workings of linear and logistic regression
Understand gradient descent in a great detail and apply it to solving problems
Learn to apply the linear models to machine learning problems and use cases
Code everything from scratch without using any ready made machine learning library

Requirements
Basic to intermediate programming skills(program flow, conditional statements, looping, object oriented approach)
Taking derivative and partial derivatives using calculus
Some basic probability and statistics
Basic linear algebra(matrix multiplication)
Description
This course will be your guide to learning how to use the power of theory, math and python to create linear regression and logistic regression, two of most popular and useful machine learning models from scratch.

This course is designed for folks with some programming experience or experienced developers looking to make the jump to data science and machine learning, I'll teach you how to dive deep into the math behind the linear models in an easy and understandable way. Once, you have understood the inner workings of the linear models and uncovered the black box, you are ready to code everything from the ground up without using any fancy ready made machine learning libraries and yes you will be taught that too! The course is beneficial for understanding the machine learning concepts deeply rather than just using some library to get results, it will guide you in the right direction for learning many other machine learning and deep learning algorithms, as this course covers all the basics required, you will be well on your way to becoming an expert Data Scientist!

Since this course goes deep into the math and has coding from scratch, a basic to intermediate knowledge of coding is a must, also good idea of derivatives(calculus), linear algebra(matrix multiplication) and basic probability is required to get the full out of this course.

Enroll today to go beyond!

Who this course is for:
This course is meant for people who want to go beyond the basic understanding of machine learning paradigms and dive deeper into the math and theory

Screenshots


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