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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