TGx:Programming Foundations of Classification and Regression LiveLessons (Machine Learning with Python for Everyone Series), Part 1

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[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/01 - Programming Foundations of Classification and Regression LiveLessons (Machine Learning with Python for Everyone Series), Part 1 (Video Training) - Introduct	141.57 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/02 - Topics.mp4	14.87 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/03 - 1.1 Environment Installation.mp4	184.76 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/04 - 1.2 Three Things You Can do with NumPy and matplotlib.mp4	283.13 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/05 - 1.3 Three Things You Can Do with Pandas.mp4	263.92 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/06 - 1.4 Three Things You Can Do with scikit-learn and Friends.mp4	242.64 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/07 - Topics.mp4	17.35 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/08 - 2.1 Probability.mp4	144.01 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/09 - 2.2 Distributions.mp4	197.95 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/10 - 2.3 Linear Combinations.mp4	464.41 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/11 - 2.4 Geometry, Part 1.mp4	291.94 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/12 - 2.5 Geometry, Part 2.mp4	379.76 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/13 - 2.6 Geometry, Part 3.mp4	116.65 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/14 - 2.7 When Computers and Math Meet.mp4	198.01 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/15 - Topics.mp4	14.51 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/16 - 3.1 Setup and the Iris Dataset.mp4	227.14 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/17 - 3.2 Accuracy.mp4	128.93 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/18 - 3.3 k-Nearest Neighbors.mp4	189.39 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/19 - 3.4 Train Test Splitting and Fitting k-NN.mp4	363.87 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/20 - 3.5 Naive Bayes.mp4	349.40 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/21 - Topics.mp4	14.59 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/22 - 4.1 Learning Evaluation.mp4	135.75 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/23 - 4.2 Resource Evaluation - Time.mp4	203.22 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/24 - 4.3 Resource Evaluation - Memory.mp4	229.46 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/25 - 4.4 Scripts.mp4	402.48 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/26 - Topics.mp4	13.41 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/27 - 5.1 Setup and the Diabetes Dataset.mp4	291.86 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/28 - 5.2 Measures of Center.mp4	165.12 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/29 - 5.3 k-Nearest Neighbors for Regression.mp4	260.33 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/30 - 5.4 Linear Regression, Part 1.mp4	451.84 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/31 - 5.5 Linear Regression, Part 2.mp4	161.38 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/32 - Topics.mp4	11.25 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/33 - 6.1 Optimization, Part 1.mp4	373.61 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/34 - 6.2 Optimization, Part 2.mp4	210.28 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/35 - 6.3 Learning Performance.mp4	129.36 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/36 - 6.4 Resource Evaluation.mp4	235.84 MB
[TutsNode.com] - Programming Foundations of Classification and Regression LiveLessons, Part 1/37 - Programming Foundations of Classification and Regression LiveLessons (Machine Learning with Python for Everyone Series), Part 1 (Video Training) - Summary.m	31.97 MB

Description

Description

Code-along sessions move you from introductory machine learning concepts to concrete code.

Machine learning is moving from futuristic AI projects to data analysis on your desk. You need to go beyond nodding along in discussion to coding machine learning tasks. These videos show you how to turn introductory machine learning concepts into concrete code using Python, scikit-learn, and friends.

You learn how to load and explore simple datasets; build, train, and perform basic learning evaluation for a few models; compare the resource usage of different models in code snippets and scripts; and briefly explore some of the software and mathematics behind these techniques.

Skill Level

Beginner

Learn How To

Build and apply simple classification and regression models
Evaluate learning performance with train-test splits
Evaluate learning performance with metrics tailored to classification and regression
Evaluate the resource usage of your learning models

Who Should Take This Course

If you are becoming familiar with the basic concepts of machine learning and you want an experienced hand to help you turn those concepts into running code, this course is for you. If you have some coding knowledge but want to see how Python can drive basic machine learning models and practice, this course is for you.

Course Requirements

A basic understanding of programming in Python (variables, basic control flow, simple scripts)

Released 2/2020