Description
Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. ML is one of the most exciting technologies that one would have ever come across.
We provide perfect combination of theory and hands-on training to make you the next-gen ML leader.
Course Curriculum
Introduction and Setup the environment
- Introduction to Python
- Introduction to Machine Learning
- Install Anaconda
Python Library for Machine Learning
- Introduction
- Getting Started with Anaconda and Jupyter
- Python for Data Analysis : Numpy
- Python for Data Analysis : Pandas
- Python for Data Visualization : Matplotlib
- Python for Data Visualization :Seaborn
- Train Your Machine :Scikit-Learn
Machine Learning: Supervised Learning-1
- Linear Regression
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Multiple Regression
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Polynomial Regression
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Regression Model Evaluation : MAE , MSE , RMSE , R2
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What is Classification ?
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Logistic Regression
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Classification Model Evaluation : Accuracy Score , Confusion Matrix , Precision , Recall
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Gradient Descent
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Cost and Loss
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Bias and Variance
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Data Prepossessing
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Feature Selection and Feature Scaling
Machine Learning: Supervised Learning-2
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k-Nearest Neighbors (AI Concept and Implementation )
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Support Vector Machine (AI Concept and Implementation)
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Decision Tree (AI Concept and Implementation)
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Random Forest (AI Concept and Implementation)
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Hyper Parameter Tuning
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Overfitting and Under-fitting
Machine Learning: Unsupervised Learning
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What is Unsupervised Learning?
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What is Clustering?
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Different Types of Clustering.
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K-MEAN Clustering (AI Concept and Implementation).
Project Covered in Data Science
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House Price Prediction
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Rainfall Prediction
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Financial Market Prediction
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Diabetic Diagnostic Prediction
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Flower Species Classification
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Titanic Survival
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Digit Classification
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Customer Segmentation
Structure your learning and get a certificate to prove it.