Machine Learning
Course Description
This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning and deep learning algorithms like SVM, Artificial Neural Network, Convolutional Neural Network. This course is designed for beginners with some programming experience or experienced developers.
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Course Curriculum
Course Content
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Section 1: Introduction
Introduction to Machine Learning
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Section 2: Python for data analysis
Numpy (Part-1)
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Numpy (Part-2)
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Pandas
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Section 3: Python for data visualization
Matplotlib (Part-1)
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Matplotlib (Part-2)
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Section 4: Linear Regression
Linear Regression (Part-1)
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Linear Regression (Part-2)
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Section 5: K Nearest Neighbors
Introduction to Supervised Learning
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K Nearest Neighbors
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Section 6: Comparing different classification models
Comparing classification models (Part-1)
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Comparing classification models (Part-2)
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Comparing classification models (Part-3)
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Section 7: K means Clustering
K-means clustering
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K-means clustering (Part-2)
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Section 8: Unsupervised Learning
Apriori Algorithm (Part-1)
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Apriori Algorithm (Part-2)
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Form for Internship/Project letter
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