| 001 Artificial-Intelligence-with-python.zip | 3.8 MB | ||
| 001 Introduction to Predictive Analysis-en.srt | 11.6 KB | ||
| 001 Introduction to Predictive Analysis.mp4 | 95.4 MB | ||
| 002 Random Forest and Extremely Random Forest-en.srt | 14 KB | ||
| 002 Random Forest and Extremely Random Forest.mp4 | 116.9 MB | ||
| 003 Dealing with Class Imbalance-en.srt | 8.2 KB | ||
| 003 Dealing with Class Imbalance.mp4 | 85.2 MB | ||
| 004 Grid Search-en.srt | 12.6 KB | ||
| 004 Grid Search.mp4 | 110.3 MB | ||
| 005 Adaboost Regressor-en.srt | 9 KB | ||
| 005 Adaboost Regressor.mp4 | 86.4 MB | ||
| 006 Predicting Traffic Using Extremely Random Forest Regressor-en.srt | 2.8 KB | ||
| 006 Predicting Traffic Using Extremely Random Forest Regressor.mp4 | 34.6 MB | ||
| 007 Traffic Prediction-en.srt | 8.3 KB | ||
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| 008 Detecting patterns with Unsupervised Learning-en.srt | 7.3 KB | ||
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| 009 Clustering-en.srt | 8.3 KB | ||
| 009 Clustering.mp4 | 69.7 MB | ||
| 010 Clustering Meanshift-en.srt | 5.8 KB | ||
| 010 Clustering Meanshift.mp4 | 55.5 MB | ||
| 011 Clustering Meanshift Continues-en.srt | 8.3 KB | ||
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| 012 Affinity Propagation Model-en.srt | 7.2 KB | ||
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| 014 Clustering Quality-en.srt | 6.3 KB | ||
| 014 Clustering Quality.mp4 | 69.9 MB | ||
| 015 Program of Clustering Quality-en.srt | 8.3 KB | ||
| 015 Program of Clustering Quality.mp4 | 70.2 MB | ||
| 016 Gaussian Mixture Model-en.srt | 5.6 KB | ||
| 016 Gaussian Mixture Model.mp4 | 62.4 MB | ||
| 017 Program of Gaussian Mixture Model-en.srt | 10 KB | ||
| 017 Program of Gaussian Mixture Model.mp4 | 91.7 MB | ||
| 018 Classification in Artificial Intelligence-en.srt | 4.3 KB | ||
| 018 Classification in Artificial Intelligence.mp4 | 21.2 MB | ||
| 019 Processing Data-en.srt | 10.3 KB | ||
| 019 Processing Data.mp4 | 65.2 MB | ||
| 020 Logistic Regression Classifier-en.srt | 3.6 KB | ||
| 020 Logistic Regression Classifier.mp4 | 16.6 MB | ||
| 021 Logistic Regression Classifier Example Using Python-en.srt | 7.7 KB | ||
| 021 Logistic Regression Classifier Example Using Python.mp4 | 61.8 MB | ||
| 022 Naive Bayes Classifier and its Examples-en.srt | 13.8 KB | ||
| 022 Naive Bayes Classifier and its Examples.mp4 | 126.5 MB | ||
| 023 Confusion Matrix-en.srt | 4.9 KB | ||
| 023 Confusion Matrix.mp4 | 52.3 MB | ||
| 024 Example os Confusion Matrix-en.srt | 6.8 KB | ||
| 024 Example os Confusion Matrix.mp4 | 45.5 MB | ||
| 025 Support Vector Machines Classifier(SVM)-en.srt | 6.3 KB | ||
| 025 Support Vector Machines Classifier(SVM).mp4 | 45 MB | ||
| 026 SVM Classifier Examples-en.srt | 8.8 KB | ||
| 026 SVM Classifier Examples.mp4 | 79 MB | ||
| 027 Concept of Logic Programming-en.srt | 14.6 KB | ||
| 027 Concept of Logic Programming.mp4 | 154.2 MB | ||
| 028 Matching the Mathematical Expression-en.srt | 8.1 KB | ||
| 028 Matching the Mathematical Expression.mp4 | 78.5 MB | ||
| 029 Parsing Family Tree and its Example-en.srt | 10.9 KB | ||
| 029 Parsing Family Tree and its Example.mp4 | 100.5 MB | ||
| 030 Analyzing Geography Logic Programming-en.srt | 6.6 KB | ||
| 030 Analyzing Geography Logic Programming.mp4 | 62.4 MB | ||
| 031 Puzzle Solver and its Example-en.srt | 7.1 KB | ||
| 031 Puzzle Solver and its Example.mp4 | 60.6 MB | ||
| 032 What is Heuristic Search-en.srt | 8.2 KB | ||
| 032 What is Heuristic Search.mp4 | 93.5 MB | ||
| 033 Local Search Technique-en.srt | 12.4 KB | ||
| 033 Local Search Technique.mp4 | 132 MB | ||
| 034 Constraint Satisfaction Problem-en.srt | 11.3 KB | ||
| 034 Constraint Satisfaction Problem.mp4 | 105 MB | ||
| 035 Region Coloring Problem-en.srt | 6.2 KB | ||
| 035 Region Coloring Problem.mp4 | 53 MB | ||
| 036 Building Maze-en.srt | 8.9 KB | ||
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| 037 Puzzle Solver-en.srt | 11.3 KB | ||
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| 038 Natural Language Processing-en.srt | 8.3 KB | ||
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| 057 Recursive Descent Parsing-en.srt | 8.5 KB | ||
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| 059 Shift Reduce Parsing-en.srt | 12.3 KB | ||
| 059 Shift Reduce Parsing.mp4 | 80.2 MB | ||
| ReadMe.txt | 204.8 B | ||
| Visit Coursedrive.org.url | 102.4 B | ||
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⚡️⚡️For More Udemy Courses Visit ???????? Course Drive
Artificial Intelligence and Predictive Analysis using Python
This course is a comprehensive understanding of AI concepts and its application using Python and iPython.
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.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.8 GB | freecoursewb | 2 weeks | 13 | 11 | |
| 2 GB | freecoursewb | 3 weeks | 27 | 34 | |
| 1.9 GB | freecoursewb | 1 month | 5 | 3 | |
| 2 GB | freecoursewb | 2 months | 15 | 8 | |
| 1.5 GB | freecoursewb | 2 months | 2 | 8 |
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