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About This Course
- Overview
Educational accomplishments and income are closely correlated. Education and skill with endorsed certificates from credible and renowned authorities typically lead to better jobs with attractive salaries. Educated and skilled workers also have lower rates of unemployment. Therefore, skills and endorsed certificates to showcase are essential for people early in their careers.
- Why Choose Imperial Academy?
Imperial Academy offers this premium Learn AI with Python course to ensure security in your career. In addition, this comprehensive Learn AI with Python course will assist you in building relevant skills that will help you find a job in the related sectors. Also, the Certificate you’ll get after completing the Learn AI with Python will put your head and shoulder above others in front of potential employers.
Become the person who would attract the results you seek. What you plant now, you will harvest later. So, grab this opportunity and start learning Learn AI with Python!
- What Imperial Academy Offers You
- QLS/ CPD/ CIQ Accredited
- 24/7 Assistance from our Support Team
- 100% Online
- Self-paced course
- Bite-sized Audio-visual Modules
- Rich Learning Materials
- Developed by Industry Specialists
- Career Guidance
- Course Design
Learn at your own pace from the comfort of your home, as the rich learning materials of this premium course is accessible from any place at any time. The advanced course curriculums are divided into tiny bite-sized audio-visual modules by industry specialists with years of experience behind them.
- Audio-visual Lessons
- Online Study Materials
Course Curriculum
-
Introduction to Predictive Analysis
00:07:00 -
Random Forest and Extremely Random Forest
00:11:00
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Dealing with Class Imbalance
00:07:00
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Grid Search
00:09:00
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Adaboost Regressor
00:08:00
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Predicting Traffic Using Extremely Random Forest Regressor
00:02:00
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Traffic Prediction
00:07:00
-
Detecting patterns with Unsupervised Learning
00:05:00
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Clustering
00:07:00
-
Clustering Meanshift
00:04:00
-
Clustering Meanshift Continues
00:06:00
-
Affinity Propagation Model
00:05:00
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Affinity Propagation Model Continues
00:05:00
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Clustering Quality
00:05:00
-
Program of Clustering Quality
00:07:00
-
Gaussian Mixture Model
00:04:00
-
Program of Gaussian Mixture Model
00:08:00
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Classification in Artificial Intelligence
00:03:00
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Processing Data
00:09:00
-
Logistic Regression Classifier
00:03:00
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Logistic Regression Classifier Example Using Python
00:07:00
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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
-
Concept of Logic Programming
00:11:00
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Matching the Mathematical Expression
00:07:00
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Parsing Family Tree and its Example
00:09:00
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Analyzing Geography Logic Programming
00:05:00
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Puzzle Solver and its Example
00:06:00
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What is Heuristic Search
00:06:00
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Local Search Technique
00:09:00
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Constraint Satisfaction Problem
00:09:00
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Region Coloring Problem
00:05:00
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Building Maze
00:07:00
-
Puzzle Solver
00:09:00
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Natural Language Processing
00:06:00
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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
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Stemming
00:07:00
-
Lemmatization
00:06:00
-
Segmentation
00:06:00
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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
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Chinking
00:07:00
-
Chunking wirh Regular Expression
00:08:00
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Named Entity Recognition
00:06:00
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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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