Introduction to Machine Learning with ENCOG 3 [2013, ENG] torrent

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Introduction to Machine Learning with ENCOG 3

Год выпуска: 2013
Производитель: Pluralsight
Сайт производителя: http://pluralsight.com/training/Courses/TableOfContents/introduction-to-machine-learning-encog
Автор: Abhishek Kumar
Продолжительность: 2h 16m
Тип раздаваемого материала: Видеоклипы
Язык: Английский
Описание: Этот курс ориентирован на внедрение и применение различных методов машинного обучения.
Машинное обучение является очень обширной областью для изучения, но этот курс сосредоточит внимание
на одном из методов машинного обучения - это нейронные сети.
Конечно же объяснение фундаментальных основ машинного обучения будет организованно через реальные приложения и
различные, связанные с ним компоненты.
В этом курсе будет рассмотрен один из опен-соурсных фреймворков в .NET, которым является ENCOG.
Также курс покажет как ENCOG вписывается в общую картину программирования систем машинного обучения.
Мы научимся создавать различные компоненты нейронной сети с использованием ENCOG и как скомбинировать эти
компоненты со сценариями реального мира.
Мы углубимся в детали упреждающих сетей и различных распространенных методик обучения поддерживаемых ENCOG.
Мы также говорим о подготовке данных для нейронных сетей с использованием процесса нормализации.
Наконец, мы проведем еще несколько тематических исследований и постараемся реализовать задачи классификации и регрессии.
Так же в этом курсе я дам некоторые советы для эффективного и быстрого построения нейронных сетей в приложениях реального мира.

This course is focused on implementation and applications of various machine learning methods.

This course is focused on implementation and applications of various machine learning methods.
As machine learning is a very vast area, this course will be targeted more towards one of the machine learning methods which is neural networks.
The course will try to make a base foundation first by explaining machine learning through some real world applications and various associated components.
In this course, we'll take one of the open source machine learning framework for .NET, which is ENCOG.
The course will explain how ENCOG fits into the picture for machine learning programming.
Then we'll learn to create various neural network components using ENCOG and how to combine these components for real world scenarios.
We'll go in detail of feed forward networks and various propagation training methodologies supported in ENCOG.
We'll also talk about data preparation for neural networks using normalization process.
Finally, we will take a few more case studies and will try to implement tasks of classification & regression.
In the course I will also give some tips & tricks for effective & quick implementations of neural networks in real world applications.
[spoiler="Содержание"]
FileName Size Length Bit rate Data rate Resolution Frame Rate Parent Folder
01.Introduction 419 KB 0:00:14 ‎128kbps 94.00 1024x768 ‎15 frames/second 01.Introduction to Machine Learning
02.Why Machine Learning 542 KB 0:00:23 ‎128kbps 60.00 1024x768 ‎15 frames/second 01.Introduction to Machine Learning
03.Why This Course 2.25 MB 0:01:42 ‎128kbps 89.00 1024x768 ‎15 frames/second 01.Introduction to Machine Learning
04.Key Concepts 1.23 MB 0:00:49 ‎128kbps 84.00 1024x768 ‎15 frames/second 01.Introduction to Machine Learning
05.Spam Filtering 933 KB 0:00:35 ‎128kbps 56.00 1024x768 ‎15 frames/second 01.Introduction to Machine Learning
06.Course Structure 1.74 MB 0:01:19 ‎128kbps 73.00 1024x768 ‎15 frames/second 01.Introduction to Machine Learning
01.Introduction 378 KB 0:00:15 ‎128kbps 106.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
02.Internet 2.03 MB 0:01:37 ‎128kbps 79.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
03.Financial Sector 1.40 MB 0:01:09 ‎128kbps 39.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
04.e-Commerce 1.77 MB 0:01:24 ‎128kbps 52.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
05.Process Industry 1.09 MB 0:00:54 ‎128kbps 35.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
06.Others 1.27 MB 0:01:02 ‎128kbps 43.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
07.Summary 0.99 MB 0:00:48 ‎128kbps 60.00 1024x768 ‎15 frames/second 02.Applications of Machine Learning
01.Introduction 929 KB 0:00:43 ‎128kbps 98.00 1024x768 ‎15 frames/second 03.Machine Learning Tasks
02.Classification 7.57 MB 0:04:35 ‎128kbps 626.00 1024x768 ‎15 frames/second 03.Machine Learning Tasks
03.Regression 5.85 MB 0:03:44 ‎128kbps 466.00 1024x768 ‎15 frames/second 03.Machine Learning Tasks
04.Clustering 5.31 MB 0:03:04 ‎128kbps 582.00 1024x768 ‎15 frames/second 03.Machine Learning Tasks
05.Summary 609 KB 0:00:28 ‎128kbps 40.00 1024x768 ‎15 frames/second 03.Machine Learning Tasks
01.Introduction 1.10 MB 0:00:50 ‎128kbps 105.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
02.Outline 0.97 MB 0:00:46 ‎128kbps 60.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
03.Human Neuron vs Artificial Neuron 2.42 MB 0:01:50 ‎128kbps 92.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
04.Neuron Computation 1.64 MB 0:01:02 ‎128kbps 84.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
05.Neural Network Component - Neuron Types 3.01 MB 0:02:11 ‎128kbps 147.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
06.Neural Network Component - Weights 1.32 MB 0:00:58 ‎128kbps 108.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
07.Neural Network Component - Activation Function 3.08 MB 0:01:29 ‎128kbps 475.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
08.Neural Network Component - Layers 2.00 MB 0:01:31 ‎128kbps 94.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
09.Neural Network Computation 4.08 MB 0:02:45 ‎128kbps 182.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
10.Model Creation 4.32 MB 0:03:28 ‎128kbps 83.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
11.Model Training 6.81 MB 0:04:27 ‎128kbps 118.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
12.Model Validation 953 KB 0:00:45 ‎128kbps 58.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
13.Summary 1.58 MB 0:01:01 ‎128kbps 105.00 1024x768 ‎15 frames/second 04.Introduction to Neural Networks
01.Introduction 322 KB 0:00:13 ‎128kbps 99.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
02.Outline 577 KB 0:00:27 ‎128kbps 31.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
03.About ENCOG 548 KB 0:00:24 ‎128kbps 54.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
04.Why ENCOG 1.84 MB 0:01:27 ‎128kbps 67.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
05.ENCOG Coverage 2.15 MB 0:01:36 ‎128kbps 142.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
06.ENCOG Resources 1.64 MB 0:01:07 ‎128kbps 175.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
07.Summary 618 KB 0:00:29 ‎128kbps 42.00 1024x768 ‎15 frames/second 05.Introduction to ENCOG 3
01.Introduction 598 KB 0:00:23 ‎128kbps 113.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
02.Outline 624 KB 0:00:30 ‎128kbps 23.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
03.Data 3.89 MB 0:03:09 ‎128kbps 98.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
04.Network 4.18 MB 0:03:08 ‎128kbps 129.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
05.Training 1.91 MB 0:01:32 ‎128kbps 77.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
06.Evaluation 900 KB 0:00:42 ‎128kbps 54.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
07.XOR Problem 844 KB 0:00:38 ‎128kbps 70.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
08.Demo - XOR problem with ENCOG 3 in C# 12.3 MB 0:07:26 ‎128kbps 377.00 1024x768 ‎15 frames/second 06.Neural Network Components in ENCOG for .NET
01.Introduction 366 KB 0:00:15 ‎128kbps 97.00 1024x768 ‎15 frames/second 07.Propagation Training
02.Outline 527 KB 0:00:25 ‎128kbps 39.00 1024x768 ‎15 frames/second 07.Propagation Training
03.Propagation Training 2.60 MB 0:01:58 ‎128kbps 99.00 1024x768 ‎15 frames/second 07.Propagation Training
04.Basic Concepts 3.66 MB 0:02:49 ‎128kbps 115.00 1024x768 ‎15 frames/second 07.Propagation Training
05.Back Propagation Algorithm 1.61 MB 0:01:15 ‎128kbps 100.00 1024x768 ‎15 frames/second 07.Propagation Training
06.Manhattan Update Rule 1.25 MB 0:00:59 ‎128kbps 83.00 1024x768 ‎15 frames/second 07.Propagation Training
07.Quick Propagation Algorithm 974 KB 0:00:39 ‎128kbps 71.00 1024x768 ‎15 frames/second 07.Propagation Training
08.Resilient Propagation Algorithm 1.92 MB 0:01:17 ‎128kbps 96.00 1024x768 ‎15 frames/second 07.Propagation Training
09.Scaled Conjugate Gradient 791 KB 0:00:37 ‎128kbps 52.00 1024x768 ‎15 frames/second 07.Propagation Training
10.Levenberg Marquardt Algorithm 1.08 MB 0:00:50 ‎128kbps 72.00 1024x768 ‎15 frames/second 07.Propagation Training
11.Demo 1.29 MB 0:00:50 ‎128kbps 71.00 1024x768 ‎15 frames/second 07.Propagation Training
12.Summary 834 KB 0:00:33 ‎128kbps 52.00 1024x768 ‎15 frames/second 07.Propagation Training
01.Introduction 788 KB 0:00:33 ‎128kbps 96.00 1024x768 ‎15 frames/second 08.Data Normalization
02.Outline 910 KB 0:00:36 ‎128kbps 55.00 1024x768 ‎15 frames/second 08.Data Normalization
03.Field Types 3.17 MB 0:02:32 ‎128kbps 93.00 1024x768 ‎15 frames/second 08.Data Normalization
04.Need Of Normalization 3.06 MB 0:02:24 ‎128kbps 99.00 1024x768 ‎15 frames/second 08.Data Normalization
05.Normalization and De-Normalization 1.87 MB 0:01:26 ‎128kbps 102.00 1024x768 ‎15 frames/second 08.Data Normalization
06.Numeric Data Field Normalization 2.60 MB 0:01:46 ‎128kbps 79.00 1024x768 ‎15 frames/second 08.Data Normalization
07.Numeric Data Field Normalization in ENCOG 2.23 MB 0:01:21 ‎128kbps 147.00 1024x768 ‎15 frames/second 08.Data Normalization
08.Nominal Data Field Normalization 3.99 MB 0:02:41 ‎128kbps 92.00 1024x768 ‎15 frames/second 08.Data Normalization
09.ENCOG Analyst 1.65 MB 0:01:13 ‎128kbps 118.00 1024x768 ‎15 frames/second 08.Data Normalization
10.Summary 898 KB 0:00:37 ‎128kbps 35.00 1024x768 ‎15 frames/second 08.Data Normalization
01.Introduction 463 KB 0:00:19 ‎128kbps 114.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
02.Outline 1.69 MB 0:01:10 ‎128kbps 41.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
03.Case Study 1 - Classification Task 2.57 MB 0:01:56 ‎128kbps 160.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
04.Flow Chart 1 2.07 MB 0:01:36 ‎128kbps 124.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
05.Demo - Case Study 1 - Shuffle 1 5.25 MB 0:02:55 ‎128kbps 282.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
06.Demo - Case Study 1 - Segregate 4.66 MB 0:02:21 ‎128kbps 415.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
07.Demo - Case Study 1 - Normalize 6.60 MB 0:03:57 ‎128kbps 393.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
08.Demo - Case Study 1 - Create Network 4.92 MB 0:03:09 ‎128kbps 278.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
09.Demo - Case Study 1 - Train Network 4.12 MB 0:02:14 ‎128kbps 659.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
10.Demo - Case Study 1 - Evaluate Network 9.16 MB 0:04:17 ‎128kbps 1357.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
11.Case Study 2 - Regression Task 2.39 MB 0:01:42 ‎128kbps 171.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
12.Flow Chart 2 2.00 MB 0:01:30 ‎128kbps 146.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
13.Demo - Case Study 1 - Shuffle 2 3.16 MB 0:01:45 ‎128kbps 234.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
14.Demo - Case Study 2 - Segregate 1.85 MB 0:00:56 ‎128kbps 352.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
15.Demo - Case Study 2 - Normalize 7.60 MB 0:02:55 ‎128kbps 834.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
16.Demo - Case Study 2 - Create Network 1.85 MB 0:01:00 ‎128kbps 249.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
17.Demo - Case Study 2 - Train Network 1.35 MB 0:00:35 ‎128kbps 514.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
18.Demo - Case Study 2 - Evaluate Network 4.98 MB 0:02:31 ‎128kbps 738.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
19.Summary 898 KB 0:00:36 ‎128kbps 39.00 1024x768 ‎15 frames/second 09.Case Studies (Classification and Regression Task)
[/spoiler]
Файлы примеров: отсутствуют
Формат видео: WMV
Видео: wmv3, 1024x768, 15fps, 23~1357 kbps
Аудио: wma2, 128kbps, Stereo, 44.1kHz
[spoiler="Скриншоты"]

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Доп. информация: Exercise includes slides and code files.