Introduction to machine learning

Part 2 of ebook "An introduction to statistical learning with applications in R" provides readers with contents including: Chapter 6 - Linear model selection and regularization; Chapter 7 - Moving beyond linearity; Chapter 8 - Tree-based methods; Chapter 9 - Support vector machines; Chapter 10 - Unsupervised learning;...

222p daonhiennhien 03-07-2024 2 1   Download

Part 2 of ebook "Introduction to artificial intelligence (Second edition)" provides readers with contents including: Chapter 8 - Machine learning and data mining; Chapter 9 - Neural networks; Chapter 10 - Reinforcement learning; Chapter 11 - Solutions for the exercises;...

178p daonhiennhien 03-07-2024 1 1   Download

Part 1 of ebook "Introduction to deep learning: From logical calculus to artificial intelligence" provides readers with contents including: Chapter 1 - From logic to cognitive science; Chapter 2 - Mathematical and computational prerequisites; Chapter 3 - Machine learning basics;...

89p daonhiennhien 03-07-2024 2 1   Download

Part 1 of ebook "Practical machine learning and image processing: For facial recognition, object detection, and pattern recognition using Python" provides readers with contents including: Chapter 1 - Setup environment; Chapter 2 - Introduction to image processing; Chapter 3 - Basics of python and scikit image;...

72p daonhiennhien 03-07-2024 2 1   Download

Artificial intelligence - Lecture 13: Machine learning. This lecture provides students with content including: introduction of machine learning; application examples of ML; key elements of a ML problem; issues in machine learning; types of learning problems;... Please refer to the detailed content of the lecture!

3p codabach1016 03-05-2024 4 2   Download

This paper discusses risk mitigation in procurement and how this could evolve over the next decade because of advances in Artificial Intelligence (AI) applications. The paper includes a literature review that covers contractors’ prequalification as a common measure for risk mitigation, a brief nontechnical introduction to AI, and the previous research related to the application of AI in contractors’ prequalification.

7p longtimenosee06 27-03-2024 1 1   Download

Ebook "Machine learning" includes content: Introduction, concept learning and the general to specific ordering; decision tree learning; artificial neural networks; evaluating hypotheses; bayesian learning; computational learning theory; instance based learning; genetic algorithms; learning sets of rules; analytical learning; combining inductive and analytical learning; reinforcement learning.

421p haojiubujain07 20-09-2023 6 4   Download

Ebook "Introduction to machine learning" includes content: Preliminaries, boolean functions, using version spaces for learning, neural networks, statistical learning, decision trees, inductive logic programming, computational learning theory, unsupervised learning,... and other contents.

209p haojiubujain07 20-09-2023 6 2   Download

Ebook "Python machine learning projects" provides readers with contents including: setting up a python programming environment an introduction to machine learning; how to build a machine learning classifier in python with scikit-learn; how to build a neural network to recognize hand written digits with tensorflow; bias-variance for deep reinforcement learning - how to build a bot for atari with openai gym;...

135p tieulangtran 28-09-2023 11 5   Download

Ebook An Introduction to Machine Learning (Second edition): Part 1 presents the following content: A Simple Machine-Learning Task; Probabilities: Bayesian Classifiers; Similarities: Nearest-Neighbor Classifiers; Inter-Class Boundaries: Linear and Polynomial Classifiers;...Please refer to the documentation for more details.

180p trankora06 12-07-2023 3 2   Download

Ebook An Introduction to Machine Learning (Second edition): Part 2 presents the following content: Induction of Voting Assemblies; Some Practical Aspects to Know About; Performance Evaluation; Induction in Multi-Label Domains; Classifiers in the Form of Rulesets;...Please refer to the documentation for more details.

168p trankora06 12-07-2023 5 1   Download

Ebook Machine learning algorithms: Part 1 presents the following content: Chapter 1: a gentle introduction to machine learning, chapter 2: important elements in machine learning, chapter 3: feature selection and feature engineering, chapter 4: linear regression, chapter 5: logistic regression, chapter 6: naive bayes, chapter 7: support vector machines.

169p runthenight09 06-05-2023 8 4   Download

Ebook Machine learning algorithms: Part 2 presents the following content: Chapter 8: decision trees and ensemble learning, chapter 9: clustering fundamentals, chapter 10: hierarchical clustering, chapter 11: introduction to recommendation systems, chapter 12: introduction to natural language processing, chapter 13: topic modeling and sentiment analysis in NLP, chapter 14: a brief introduction to deep learning and tensorflow, chapter 15: creating a machine learning architecture.

184p runthenight09 06-05-2023 8 4   Download

Ebook Introduction to computation and programming using Python: Part 2 include of the following content: chapter 11 plotting and more about classes; chapter 12 stochastic programs, probability, and statistics; chapter 13 random walks and more about data visualization; chapter 14 monte carlo simulation; chapter 15 understanding experimental data; chapter 16 lies, damned lies, and statistics; chapter 17 knapsack and graph optimization problems; chapter 18 dynamic programming; chapter 19 a quick look at machine learning.

158p runthenight03 07-12-2022 23 5   Download

Lecture Introduction to Machine learning and Data mining: Lesson 1. This lesson provides students with content about: data collection and currency processing; recovery time; reporting data collection system; extract semantic symbols; convert data text;... Please refer to the detailed content of the lecture!

30p hanlamcoman 26-11-2022 17 5   Download

Lecture Introduction to Machine learning and Data mining: Lesson 3. This lesson provides students with content about: unsupervised learning; clustering; basic learning problems; partition-based clustering; evaluation of clustering quality;... Please refer to the detailed content of the lecture!

30p hanlamcoman 26-11-2022 16 5   Download

Lecture Introduction to Machine learning and Data mining: Lesson 4. This lesson provides students with content about: supervised learning; K-nearest neighbors; neighbor-based learnin; multiclass classification/categorization; distance/similarity measure;... Please refer to the detailed content of the lecture!

23p hanlamcoman 26-11-2022 17 5   Download

Lecture Introduction to Machine learning and Data mining: Lesson 7. This lesson provides students with content about: evaluation of empirical results; assessing performance; some evaluation techniques; hold-out (random splitting); K-fold cross-validation;... Please refer to the detailed content of the lecture!

26p hanlamcoman 26-11-2022 10 5   Download

Lecture Introduction to Machine learning and Data mining: Lesson 9.2. This lesson provides students with content about: probabilistic modeling; expectation maximization; intractable inference; the Baum-Welch algorithm;... Please refer to the detailed content of the lecture!

20p hanlamcoman 26-11-2022 10 5   Download

Lecture Introduction to Machine learning and Data mining: Lesson 10. This lesson provides students with content about: regularization; revisiting overfiting; the bias-variance decomposition; bias-variance tradeoff; regularization in ridge regression; regularization in lasso;... Please refer to the detailed content of the lecture!

25p hanlamcoman 26-11-2022 10 5   Download