Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.
Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.
Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.
• Discussion about Box-plot and Outlier
• Goal: Increase Profits of a Store
• Areas of increasing the efficiency
• Data Request
• Business Problem: To maximise shop Profits
• What are Interlinked variables
• What is Strategy
• Interaction b/w the Variables
• Univariate analysis
• Multivariate analysis
• Bivariate analysis
• Relation b/w Variables
• Standardise Variables
• What is Hypothesis?
• Interpret the Correlation
• Negative Correlation
• Machine Learning
Data analysis has two prominent methods: qualitative research and quantitative research. Each method has their own techniques. Interviews and observations are forms of qualitative research, while experiments and surveys are quantitative research.
• Correlation b/w Nominal Variables
• Contingency Table
• What is Expected Value?
• What is Mean?
• How Expected Value differs from Mean
• Experiment – Controlled Experiment, Uncontrolled Experiment
• Degree of Freedom
• Dependency b/w Nominal Variable & Continuous Variable
• Linear Regression
• Extrapolation and Interpolation
• Univariate Analysis for Linear Regression
• Building Model for Linear Regression
• Pattern of Data means?
• Data Processing Operation
• What is sampling?
• Sampling Distribution
• Stratified Sampling Technique
• Disproportionate Sampling Technique
• Balanced Allocation-part of Disproportionate Sampling
• Systematic Sampling
• Cluster Sampling
Comparative evaluation of Machine Learning. (ML) systems used for Information Extraction.
• Multi variable analysis
• linear regression
• Simple linear regression
• Hypothesis testing
• Speculation vs. claim(Query)
• Sample
• Step to test your hypothesis
• performance measure
• Generate null hypothesis
• alternative hypothesis
• Testing the hypothesis
• Threshold value
• Hypothesis testing explanation by example
• Null Hypothesis
• Alternative Hypothesis
• Probability
• Histogram of mean value
• Revisit CHI-SQUARE independence test
• Correlation between Nominal Variable
Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data
• Machine Learning
• Importance of Algorithms
• Supervised and Unsupervised Learning
• Various Algorithms on Business
• Simple approaches to Prediction
• Predict Algorithms
• Population data
• sampling
• Disproportionate Sampling
• Steps in Model Building
• Sample the data
• What is K?
• Training Data
• Test Data
• Validation data
• Model Building
• Find the accuracy
• Rules
• Iteration
• Deploy the model
• Linear regression
Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events.
• Clustering
• Cluster and Clustering with Example
• Data Points, Grouping Data Points
• Manual Profiling
• Horizontal & Vertical Slicing
• Clustering Algorithm
• Criteria for take into Consideration before doing Clustering
• Graphical Example
• Clustering & Classification: Exclusive Clustering, Overlapping Clustering, Hierarchy
Clustering
• Simple Approaches to Prediction
• Different types of Distances: 1.Manhattan, 2.Euclidean, 3 Consine Similarity
• Clustering Algorithm in Mahout
• Probabilistic Clustering
• Pattern Learning
• Nearest Neighbour Prediction
• Nearest Neighbour Analysis