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Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis.
Data Aggregation
Data Mining

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Click on this link for full playlist of Machine Learning:
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Learn Machine Learning here with ease from basics. Many examples are discussed to explain topic with clear understanding.
This section contains following topics in detail:
* What is Machine Learning?
* Machine Learning- Analytics
* Descriptive Analytics
* Predictive Analytics
* Prescriptive Analytics
* Relation between Artificial Intelligence and Machine Learning
* Importance of Machine Learning
* Evolution of Machine Learning
* Benefits of Machine Learning
* Real Life Examples of Machine Learning
* Types of Machine Learning
* Supervised Learning
* Unsupervised Learing
* Classification
* Classification Examples
* Technique to solve Classification Problems
* Decision Tree
* Formula of Entropy
* k- Nearest Neighbor(kNN) Algorithm
* Support Vector Machine(SVM)
* How Support Vector Machine Works?
* What is best Hyperplane?
* How to separate Vectors?
* Kernel Function in Support Vector Machine(SVM)
* Regression
* Types of Regression
* Linear Regression
* How to determine Weights and Bias?
* Logistic Regression
* Ensemble
* About Ensemble Method
* Ensemble by Voting
* Boosting
* Random Forest
* Association Analysis
* Key Metrics in Associaton Analysis
* Support- Association Rule
* Confidence- Association Rule
* Lift- Association Rule
* Apriori Algorithm
* Mining Rules
* Clustering
* Types of Clustering Techniques
* Types of Cluster
* Implementation of Clustering
* Process of Finding Clusters
* k means Clustering
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