* 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: Machine Learning for Software Engineers  (Lida 118 vezes)

0 Membros e 1 Visitante estão a ver este tópico.

Online mitsumi

  • Moderador Global
  • ***
  • Mensagens: 115810
  • Karma: +0/-0
Machine Learning for Software Engineers
« em: 14 de Julho de 2021, 16:07 »

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 5.96 GB | Duration: 11h 30m
A Practical Approach

What you'll learn
Theory and practicals of Regression
Theory and practicals of Classification
Theory and practicals of Clustering
Exploratory Data Analysis techniques

Description
This course has been put together by a team of experienced teaching professionals and industry experts in machine learning.

We aim to offer software engineers and those with some coding experience an introduction to the main concepts of machine learning.

We take a very practical approach, mixing theory videos and practical videos, with all code and jupyter notebooks used throughout the course being available for download. We begin with Regression, then Exploratory Data Analysis, before moving on to Classification and Clustering.

Not only will you learn how to build models, you'll also learn the correct ways to evaluate your data, identify problems and validate the correctness of your models.

At the end of this course you will be able to:

Analyse a new set of data using Exploratory Data Analysis

Generate summary statistics and visualisations

Identify outliers and be able to handle missing data

Be able to use: jupyter, pandas, seaborn, matDescriptionlib, scipy, imblearn

Build Linear Regression models - Ordinary Least Squares

Build Non-Linear Regression models - SVM, Decision Trees, Random Forest

Build Classification models - K-Nearest Neighbour, Approximate KNN, Naive Bayes

Build Clustering models - K-means, Gaussian Mixture Models, Agglomerative Clustering, DBSCAN

Data resampling techniques, dummy classifiers & k-fold validation, Pipelines

Data encoding techniques - One-hot Encoding, Target Encoding, Binary Encoding

This course includes:

Over 11 hours of video content

17 downloadable resources

17 practical assignments in jupyter notebooks

Reference Materials & further reading

Who this course is for:
Coders who are looking to learn or brush up on some practical Machine Learning skills
Developers who are interested in Machine Learning
Developers who are interested in Data Science

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