[ FreeCourseWeb ] Machine Learning using Python - Udemy

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[ FreeCourseWeb.com ] Machine Learning using Python - Udemy
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 01 Introduction
    • 001 Introduction Machine Learning Using Python.en.srt (12.9 KB)
    • 001 Introduction Machine Learning Using Python.mp4 (43.2 MB)
    02 Usage of Machine Learning Packages in Python
    • 001 Installation of Python.en.srt (8.5 KB)
    • 001 Installation of Python.mp4 (58.4 MB)
    • 002 Example of Machine Learning Using Python.en.srt (8.6 KB)
    • 002 Example of Machine Learning Using Python.mp4 (58.0 MB)
    • 003 Example of Machine Learning Using Python Continues.en.srt (4.4 KB)
    • 003 Example of Machine Learning Using Python Continues.mp4 (29.6 MB)
    03 Linear Regression
    • 001 Linear Regression in ML.en.srt (10.5 KB)
    • 001 Linear Regression in ML.mp4 (71.6 MB)
    • 002 Linear Regression Example.en.srt (8.2 KB)
    • 002 Linear Regression Example.mp4 (54.4 MB)
    • 003 Linear Regression Example Continues.en.srt (9.7 KB)
    • 003 Linear Regression Example Continues.mp4 (68.0 MB)
    • 004 Support Vector Algorithm in ML.en.srt (8.7 KB)
    • 004 Support Vector Algorithm in ML.mp4 (70.6 MB)
    04 Classifier and Python Package
    • 001 Decision Tree Classifier.en.srt (7.6 KB)
    • 001 Decision Tree Classifier.mp4 (58.7 MB)
    • 002 Random Forest Classification.en.srt (6.8 KB)
    • 002 Random Forest Classification.mp4 (50.5 MB)
    • 003 K Mean Clustering.en.srt (10.3 KB)
    • 003 K Mean Clustering.mp4 (59.2 MB)
    • 004 Apriori Python Package.en.srt (10.8 KB)
    • 004 Apriori Python Package.mp4 (63.6 MB)
    • 005 Apriori Python Package Continues.en.srt (8.8 KB)
    • 005 Apriori Python Package Continues.mp4 (28.6 MB)
    05 Evaluation Metrics
    • 001 Evaluation Metrics.en.srt (9.8 KB)
    • 001 Evaluation Metrics.mp4 (52.9 MB)
    • 002 Example of Evaluation Metrics.en.srt (8.8 KB)
    • 002 Example of Evaluation Metrics.mp4 (84.9 MB)
    • 003 Confusion Matix in Evaluation Metrics.en.srt (8.4 KB)
    • 003 Confusion Matix in Evaluation Metrics.mp4 (46.8 MB)
    • 004 Classification Reports in Evaluation Metrics.en.srt (10.8 KB)
    • 004 Classification Reports in Evaluation Metrics.mp4 (99.7 MB)
    • 005 Example of MAE, MSE and Variance using Evaluation Metrics.en.srt (10.0 KB)
    • 005 Example of MAE, MSE and Variance using Evaluation Metrics.mp4 (61.9 MB)
    • 006 Sea Born Example using Evaluation Metrics.en.srt (6.4 KB)
    • 006 Sea Born Example using Evaluation Metrics.mp4 (51.6 MB)
    • 007 Scatter Matrix using Evaluation Metrics.en.srt (3.9 KB)
    • 007 Scatter Matrix using Evaluation Metrics.mp4 (26.8 MB)
    06 Missing Value
    • 001 Handling Missing Values in Python.en.srt (13.5 KB)
    • 001 Handling Missing Values in Python.mp4 (55.2 MB)
    • 002 Handling Missing Values in Python Continues.en.srt (9.0 KB)
    • 002 Handling Missing Values in Python Continues.mp4 (61.0 MB)
    • 003 Exception Handling in Python.en.srt (9.5 KB)
    • 003 Exception Handling in Python.mp4 (48.1 MB)
    • 004 More on Exception Handling in Python.en.srt (8.2 KB)
    • 004 More on Exception Handling in Python.mp4 (47.8 MB)
    • Bonus Resources.txt (0.3 KB)

Description

Machine Learning using Python - Udemy

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.31 GB | Duration: 3h 18m
Learn to create Machine Learning Algorithms in Python from Data Science experts. Machine Learning simplified with python
What you'll learn
The students will learn What is Machine Learning. Its Intro – why its used, Data Science defined), Analytics Defined (Predictive, Prescriptive etc.,), Data Mining Flow(Phases defined – with Modeling phase that involves ML).
Also Learn the explanation on Data Set Supervised Learning, Unsupervised Learning, Classification Algorithms, Regression Algorithms.
Learn about Linear Regression, Logistic Regression, Naive Bayes Classifier, Anonymous Detection, Decision Trees, Random Forest, Neural Networks, K-Means Clustering Apriori algorithm.
Learn Feature Selection, Support Ventor Machine, Basic explanation on Use Cases Basic Functions defines (Cost function, likelihood function, normalization, trade off etc.,)
Learn Primary tools/ Softwares used for ML Python Packages for Machine Learning

Description
Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making. This training is an introduction to the concept of machine learning, its algorithms and application using Python.

The training will include the following;

What is Machine Learning? (Intro – why its used, Data Science defined)

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1.3 GB
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[ FreeCourseWeb ] Machine Learning using Python - Udemy

Torrent hash: B4A2A1FB137430C94DE17BAD849B0249D6D09EE2