Section 01: Introduction | |||
Introduction to Predictive Analysis | 00:09:00 | ||
Random Forest and Extremely Random Forest | 00:11:00 | ||
Section 02: Class Imbalance and Grid Search | |||
Dealing with Class Imbalance | 00:07:00 | ||
Grid Search | 00:09:00 | ||
Section 03: Adaboost Regressor | |||
Adaboost Regressor | 00:08:00 | ||
Predicting Traffic Using Extremely Random Forest Regressor | 00:02:00 | ||
Traffic Prediction | 00:07:00 | ||
Section 04: Detecting patterns with Unsupervised Learning | |||
Detecting patterns with Unsupervised Learning | 00:05:00 | ||
Clustering | 00:07:00 | ||
Clustering Meanshift | 00:04:00 | ||
Clustering Meanshift Continues | 00:06:00 | ||
Section 05: Affinity Propagation Model | |||
Affinity Propagation Model | 00:05:00 | ||
Affinity Propagation Model Continues | 00:05:00 | ||
Section 06: Clustering Quality | |||
Clustering Quality | 00:05:00 | ||
Program of Clustering Quality | 00:07:00 | ||
Section 07: Gaussian Mixture Model | |||
Gaussian Mixture Model | 00:04:00 | ||
Program of Gaussian Mixture Model | 00:08:00 | ||
Section 08: Classifiers | |||
Classification in Artificial Intelligence | 00:03:00 | ||
Processing Data | 00:09:00 | ||
Logistic Regression Classifier | 00:03:00 | ||
Logistic Regression Classifier Example Using Python | 00:07:00 | ||
Naive Bayes Classifier and its Examples | 00:11:00 | ||
Confusion Matrix | 00:04:00 | ||
Example os Confusion Matrix | 00:06:00 | ||
Support Vector Machines Classifier(SVM) | 00:05:00 | ||
SVM Classifier Examples | 00:08:00 | ||
Section 09: Logic Programming | |||
Concept of Logic Programming | 00:11:00 | ||
Matching the Mathematical Expression | 00:07:00 | ||
Parsing Family Tree and its Example | 00:09:00 | ||
Analyzing Geography Logic Programming | 00:05:00 | ||
Puzzle Solver and its Example | 00:06:00 | ||
Section 10: Heuristic Search | |||
What is Heuristic Search | 00:06:00 | ||
Local Search Technique | 00:09:00 | ||
Constraint Satisfaction Problem | 00:09:00 | ||
Region Coloring Problem | 00:05:00 | ||
Building Maze | 00:07:00 | ||
Puzzle Solver | 00:09:00 | ||
Section 11: Natural Language Processing | |||
Natural Language Processing | 00:06:00 | ||
Examine Text Using NLTK | 00:04:00 | ||
Raw Text Accessing (Tokenization) | 00:11:00 | ||
NLP Pipeline and Its Example | 00:07:00 | ||
Regular Expression with NLTK | 00:05:00 | ||
Stemming | 00:07:00 | ||
Lemmatization | 00:06:00 | ||
Segmentation | 00:06:00 | ||
Segmentation Example | 00:03:00 | ||
Segmentation Example Continues | 00:04:00 | ||
Information Extraction | 00:09:00 | ||
Tag Patterns | 00:03:00 | ||
Chunking | 00:09:00 | ||
Representation of Chunks | 00:05:00 | ||
Chinking | 00:07:00 | ||
Chunking wirh Regular Expression | 00:08:00 | ||
Named Entity Recognition | 00:06:00 | ||
Trees | 00:07:00 | ||
Context Free Grammar | 00:03:00 | ||
Recursive Descent Parsing | 00:06:00 | ||
Recursive Descent Parsing Continues | 00:06:00 | ||
Shift Reduce Parsing | 00:08:00 | ||
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