Overview / Usage

Machine Learning with oneAPI – A Practical Approach

Note: All the implementations are to be demoed with the Intel DevCloud

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1. Intel oneAPI – An introductory discussion.

a. Why oneAPI?

b. What is there for us with oneAPI?

c. Features and learning resources.

1. Intel oneAPI – Toolkits – An exploratory analysis.

a. Intel oneAPI toolkits

b. Details in brief about all the tool kits.

c. References and learning materials.

1. Intel DevCloud – Get everything onto cloud.

a. Power of DevCloud

b. Registration process

c. Jupyter notebook and DevCloud

d. DevCloud Commands

1. What is Machine Learning? – Introduction.

a. Types of Machine Learning with examples

b. The ML framework

c. Deep Learning vs. Machine Learning.

d. Where to use Machine Learning and where Deep Learning?

1. The Tools and Pre-requisites

a. The under- and over-fitting, regularization, and cross-validation.

b. Intel Extension for Scikit-learn

c. Examples and usage.

1. Supervised Learning

a. Introduction to Supervised Learning

b. What is regression?

c. Where is regression useful?

d. Steps in regression.

e. Classification problems.

f. K-Nearest Neighbors Walk through and implementation

g. Linear vs. Logistic Regression

h. The metrics - cost functions, regularization, feature selection, and hyper-parameters

i. The importance of bias and variance.

1. Support Vector Machines

a. What is SVM?

b. How does it work?

c. Implementation and testing

d. Cost functions of SVM

1. Decision Trees

a. What are Decision Trees all about?

b. Classification problem with decision trees.

c. Random Forest Classifier or Decision Trees?

d. Implementation.

1. Bagging

a. Why is bagging important?

b. Variance and Bagging – What’s the connect?

c. Implementation

1. Boosting and Stacking

a. Variance and Boosting – What is the connect?

1. Unsupervised Learning techniques

a. Clustering techniques.

b. Dimensionality reduction.

1. Advanced AI Tool Kits.

a. Intel AI Analytics Tool Kit

b. Intel OpenVINO

c. Intel Distribution for Python

d. Intel Machine Learning Tool Kits.

1. Case studies.

Methodology / Approach

It is an authored volume of book

Technologies Used

oneAPI, oneDAL, oneDNN, DevCloud

Repository

https://github.com/shriramkv/MachineLearningwithoneAPI