[UDEMY] Artificial Intelligence and Predictive Analysis using Python - [FTU]
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Files
| 01-Random Forest and Extremely Random Forest.mp4 | 198.8 MB | ||
| 02-Dealing with Class Imbalance.mp4 | 143.4 MB | ||
| 03-Grid Search.mp4 | 186.5 MB | ||
| 04-Adaboost Regressor.mp4 | 146.1 MB | ||
| 05-Predicting Traffic Using Extremely Random Forest Regressor.mp4 | 57.7 MB | ||
| 06-Traffic Prediction.mp4 | 139.6 MB | ||
| 07-Detecting patterns with Unsupervised Learning.mp4 | 127.1 MB | ||
| 08-Clustering.mp4 | 119.1 MB | ||
| 09-Clustering Meanshift.mp4 | 94.3 MB | ||
| 10-Clustering Meanshift Continues.mp4 | 103.5 MB | ||
| 11-Affinity Propagation Model.mp4 | 127.9 MB | ||
| 12-Affinity Propagation Model Continues.mp4 | 80.6 MB | ||
| 13-Clustering Quality.mp4 | 118.7 MB | ||
| 14-Program of Clustering Quality.mp4 | 119.8 MB | ||
| 15-Gaussian Mixture Model.mp4 | 106.4 MB | ||
| 16-Program of Gaussian Mixture Model.mp4 | 152.5 MB | ||
| 17-Classification in Artificial Intelligence.mp4 | 35.6 MB | ||
| 18-Processing Data.mp4 | 111 MB | ||
| 19-Logistic Regression Classifier.mp4 | 27.5 MB | ||
| 20-Logistic Regression Classifier Example Using Python.mp4 | 106.7 MB | ||
| 21-Naive Bayes Classifier and its Examples.mp4 | 213.4 MB | ||
| 22-Confusion Matrix.mp4 | 88.2 MB | ||
| 23-Example os Confusion Matrix.mp4 | 77.9 MB | ||
| 24-Support Vector Machines Classifier(SVM).mp4 | 72.7 MB | ||
| 25-SVM Classifier Examples.mp4 | 132.8 MB | ||
| 26-Concept of Logic Programming.mp4 | 263.7 MB | ||
| 27-Matching the Mathematical Expression.mp4 | 131.3 MB | ||
| 28-Parsing Family Tree and its Example.mp4 | 167 MB | ||
| 29-Analyzing Geography Logic Programming.mp4 | 106.4 MB | ||
| 30-Puzzle Solver and its Example.mp4 | 100.9 MB | ||
| 31-What is Heuristic Search.mp4 | 155 MB | ||
| 32-Local Search Technique.mp4 | 217.3 MB | ||
| 33-Constraint Satisfaction Problem.mp4 | 178 MB | ||
| 34-Region Coloring Problem.mp4 | 88.7 MB | ||
| 35-Building Maze.mp4 | 131.6 MB | ||
| 36-Puzzle Solver.mp4 | 178 MB | ||
| 37-Natural Language Processing.mp4 | 114.4 MB | ||
| 38-Examine Text Using NLTK.mp4 | 98.6 MB | ||
| 39-Raw Text Accessing (Tokenization).mp4 | 202.5 MB | ||
| 40-NLP Pipeline and Its Example.mp4 | 126.6 MB | ||
| 41-Regular Expression with NLTK.mp4 | 83.8 MB | ||
| 42-Stemming.mp4 | 119 MB | ||
| 43-Lemmatization.mp4 | 126.3 MB | ||
| 44-Segmentation.mp4 | 159.5 MB | ||
| 45-Segmentation Example.mp4 | 38.7 MB | ||
| 46-Segmentation Example Continues.mp4 | 46.2 MB | ||
| 47-Information Extraction.mp4 | 83.8 MB | ||
| 48-Tag Patterns.mp4 | 75 MB | ||
| 49-Chunking.mp4 | 175.8 MB | ||
| 50-Representation of Chunks.mp4 | 114 MB | ||
| 51-Chinking.mp4 | 150 MB | ||
| 52-Chunking wirh Regular Expression.mp4 | 163.3 MB | ||
| 53-Named Entity Recognition.mp4 | 133.5 MB | ||
| 54-Trees.mp4 | 101.8 MB | ||
| 55-Context Free Grammar.mp4 | 63.5 MB | ||
| 56-Recursive Descent Parsing.mp4 | 113.3 MB | ||
| 57-Recursive Descent Parsing Continues.mp4 | 72.9 MB | ||
| 58-Introduction to Predictive Analysis.mp4 | 162.6 MB | ||
| 59-Shift Reduce Parsing.mp4 | 134.7 MB | ||
| Discuss.FreeTutorials.Us.html | 165.7 KB | ||
| FreeCoursesOnline.Me.html | 108.3 KB | ||
| FreeTutorials.Eu.html | 102.2 KB | ||
| How you can help Team-FTU.txt | 307.2 B | ||
| Torrent Downloaded From GloDls.to.txt | 102.4 B | ||
| [TGx]Downloaded from torrentgalaxy.org.txt | 512 B | ||
| vz | 0 B | ||
| ▲ 66 total files | |||
Description
This course is a comprehensive understanding of AI concepts and its application using Python and iPython .
Created by : EDU CBA
Last updated : 12/2018
Language : English
Torrent Contains : 66 Files, 12 Folders
Course Source : https://www.udemy.com/artificial-intelligence-with-python/
What you'll learn
• Learn What is Artificial Intelligence, Intelligence and Applications of AI.
• Learn Problem solving using AI, AI search algorithms, Informed (Heuristic) Search Strategies.
• Learn Local Search Algorithms, Learning System, and Common Sense
• Learn Genetic algorithms, Expert Systems, and Scikit-learn module
Requirements
• Basic knowledge of Python
• Beginner knowledge of Statistics
Description
Artificial intelligence is the simulation of human intelligence through machines and mostly through computer systems. Artificial intelligence is a sub field of computer. It enables computers to do things which are normally done by human beings. This course is a comprehensive understanding of AI concepts and its application using Python and iPython.
The training will include the following :
What is Artificial Intelligence?
• Intelligence
• Applications of AI
• Problem solving
• AI search algorithms
• Informed (Heuristic) Search Strategies
• Local Search Algorithms
• Learning System
• Common Sense
• Genetic algorithms
• Expert Systems
• Scikit-learn module
Who this course is for :
• Students and professionals who are interested in learning robotics and bio metrics.
• People who are very keen about learning Artificial Intelligence.
For More Udemy Free Courses >>> http://www.freetutorials.eu
For more Lynda and other Courses >>> https://www.freecoursesonline.me/
Our Forum for discussion >>> https://discuss.freetutorials.eu/ 
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