- Artificial Intelligence
- 270 (Registered)
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(4 Reviews)
Course Content
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Introduction to Data Science This is an overall introduction about Artificial Intelligence, Machine Learning and Data Science
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Python for Data Science
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Descriptive Statistics
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Introduction to Pandas
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Introduction to Numpy
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Data Distribution
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Inferential Statistics
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Statistics in Machine Learning
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Bi-variate Covariance and Correlation
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Bi-variate Chi-square Test
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Bi-variate Anova Test
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Linear Regression Assumption
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Multiple Linear Regression
- Data Science Model Building Process
- Introduction to Multiple Linear Regression
- Exploratory Data Analysis (EDA) Quality issues
- Exploratory Data Analysis (EDA) Fixing Nulls
- Exploratory Data Analysis (EDA) Label Encoding
- Multiple Linear Regression Model Building
- Learning Curve
- Bias-Variance Trade Off
- Code Files
- Quiz-13
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Polynomial Regression
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Normal Equation Solver
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EDA and Model Building Pipeline
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Gradient Descent
- Gradient Descent Explanation
- Gradient Descent Logits
- Gradient Descent Math
- Gradient Descent Convergence and Divergence
- Issues with Gradient Descent
- Stochastic Gradient Descent (SGD) Introduction
- SGD Gradient Calculation
- Understanding SGD Intuitives
- SGD scikitlearn Tuning
- SGD Finetuning Grid Search
- Code Files
- Quiz-17
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Regularization and Feature Selection
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Classification-Logistic Regression - I
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Logistic Regression - II
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Classification - Multi Class
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K Nearest Neighbor (KNN)
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Classification - Multi Label Output
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Support Vector Machine (SVM)
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Linear Algebra - III
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Dimensionality Reduction
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Clustering
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Decision Tree
- Introduction to Decision Trees
- Decision Tree Classification Impurity Measures
- Decision Tree Building Prediction
- Overfitting Problem
- Pro & Cons of Feature Selection Approach
- Decision Tree Pruning and Conclusion
- Decision Tree Classifier SciKit Learn
- Decision Tree Regressor Introduction
- Decision Tree Regressor Recursive Binary Split
- Decision Tree Regression Scikit Learn
- Code Files
- Quiz-28
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Ensemble Models
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Anomaly Detection
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Natural Language Processing (NLP)
Instructor
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This course we can't say online it is more than online like can say Classroom training. Course content is in depth with clear explanation of maths behind the functionality. This is made for all levels of ehnthusiastics in learning new things, and exploring themselves. This course creates more interest and well structured manner. Never ever find such course anywhere. Thanks Rama Raju Garu.
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Best Institute for Machine Learning
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All the topics are explained well and connected all the dots (like, stats, math and algorithms) very well by Rama Raju Sir. I'd suggest this module for all the freshers and experienced IT professionals who are new to Data Science/Machine Learning and AI.
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Best Online course
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