Top 5 Machine Learning Introduction Slides for Beginners

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In this post, you will get to know a list of introduction slides (ppt) for machine learning. These slides could help you understand different types of machine learning algorithms with detailed examples. One or more slides from the following list could be used for making presentations on machine learning. If you are looking out for topics to be included in the machine learning course for your internal training purpose in your organization, the details presented below might turn out to be very helpful. If you are starting on learning data science, these could be good slides.

Machine Learning Overview

Machine Learning: An Overview: The slides present introduction to machine learning along with some of the following:

  1. Different types of learning (supervised, unsupervised, reinforcement)
  2. Dimensions of a learning system (different types of feedback, representation, use of knowledge)
  3. Supervised learning algorithms such as Decision tree, neural network, support vector machines (SVM), Bayesian network learning, nearest neighbor models
  4. Reinforcement learning
  5. Unsupervised learning

Introduction to Supervised Learning

supervised learning slides sample

Figure: Supervised Learning Overview

These are some supervised machine learning slides describing concepts of supervised learning (a type of machine learning) with examples. The following are covered in the slides:

  1. What is meant by “Learning”?
  2. Difference between supervised and unsupervised learning
  3. Different machine learning algorithms for supervised learning
    1. Decision tree (information gain theory, entropy, handling overfitting, and other issues)
    2. Model evaluation methods (hold-out, n-fold cross-validation, Leave-one-out cross-validation, validation set)
    3. Classification measures (precision, recall, F1 score, ROC curve, Sensitivity, Specificity, AUC, Scoring and ranking technique, ranking and lift analysis)
    4. Naive Bayes
    5. Support vector machines
    6. K-nearest neighbors

Introduction to Machine Learning

introduction to machine learning

figure: Glimpse of Data Mining Methods

These machine learning slides represent good information on introduction to machine learning using some of the following concepts:

  • Data Mining and Knowledge Discovery
  • Data Mining Methods
  • Supervised Learning
  • Unsupervised Learning
  • Other Learning Paradigms
  • Introduction to Data Preprocessing

Machine Learning and Neural Networks

Machine learning neural network slides

Figure: Artificial Neuron

These machine learning and neural networks slides represent some of the following concepts:

  • Introduction to Machine learning
  • Machine learning algorithms
    • KNN
    • Winnow algorithm
    • Naive Bayes
    • Decision trees
    • Reinforcement learning
    • Genetic algorithm
  • Neural network concepts
    • Concepts of neurons, perceptron
    • Recurrent networks
    • Backpropagation
    • Hopfield network
    • Self-organizing networks

Introduction to Deep Learning (Andrew NG)

deep learning slides by andrew ng

Figure: Features for Machine Learning

Those looking to get a high-level overview of deep learning would find these deep learning slides (could be used as both ppt and pdf) by Andrew NG very useful. The following topics are covered in the presentation:

  • Introduction to machine learning / deep learning with examples
  • Examples of features for machine learning
  • Introduction to neural networks, deep learning
  • Deep learning applications examples

The slides on the machine learning course on Coursera by Andrew NG could be downloaded using Coursera-DL utility.

Summary

In this post, you got information about some good machine learning slides/presentations (ppt) covering different topics such as an introduction to machine learning, neural networks, supervised learning, deep learning etc. If you are beginning on learning machine learning, these slides could prove to be a great start. Please feel free to share great slides information if you know about them.

 

Ajitesh Kumar

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

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