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Author: Joseph B. Wright Publisher: ISBN: 9781925114294 Category : Languages : en Pages :
Book Description
The Maths Mate Orange Student Pad is part of the popular Maths Mate Program, which was originally published in 1995. The program's success over more than two decades is due to its unique design, allowing the review and gradual development of basic skills.
Author: Joseph B. Wright Publisher: ISBN: 9781925114294 Category : Languages : en Pages :
Book Description
The Maths Mate Orange Student Pad is part of the popular Maths Mate Program, which was originally published in 1995. The program's success over more than two decades is due to its unique design, allowing the review and gradual development of basic skills.
Author: Joseph B. Wright Publisher: ISBN: 9781925114300 Category : Languages : en Pages :
Book Description
The Maths Mate Rose Student Pad is part of the popular Maths Mate Program, which was originally published in 1995. The program's success over more than two decades is due to its unique design, allowing the review and gradual development of basic skills.
Author: Madhubun Publisher: Vikas Publishing House ISBN: 9352719697 Category : Mathematics Languages : en Pages :
Book Description
1. It is a series of eight textbooks for Classes 1 to 8 that conforms to the vision of National Curriculum Framework and is written in accordance with the latest syllabus of the CBSE. 2. Learning Objectives: Lists well what a learner will know and be able to do after studying the chapter. 3. Let’s Recall: Refreshes the concepts learnt in the form of a revision exercise to brush up the concepts taught in previous chapters or grades. 4. Let’s Begin: Introduction to the chapter. 5. My Notes: Tips to help the learner remember the important points/formulae taught in the chapter. 6. Let’s Try: Simple straight forward questions for quick practice while studying any topic based on the first two levels of Bloom’s Taxonomy —Knowledge and Understanding. 7. Error Alarm: Common mistakes which learners commit often along with the correct way of doing the same. 8. Know More: Additional information for the learners relating to the concepts learnt in the chapter 9. Maths in My Life includes questions relating Maths to daily life and which can help relate the topic with the environment (life) around us. 10. Tricky Maths: Challenge questions to help the learners build thinking skills and reasoning skills by solving tricky questions. 11. Project Work: Projects which can help learners connect Math with our daily life or that take the concepts learnt to a new level. 12. Concept Map: Summary points to list the important concepts learnt in the chapter in a crisp form. 13. Test Zone: Revision exercise of the concepts learnt in the chapter. This includes both objective and subjective type of questions. 14. Mental Maths: Maths problems for performing faster calculations mentally. 15. Maths Master: Involves deep critical thinking of learners about any topic, concept, relation, fact or anything related to that chapter. May have open ended questions or extension of the topic. 16. Application in Real-Life: Every chapter in each book also explains how and where it is used in daily life. 17. In the Lab: Math lab activities for helping the learners understand the concepts learnt through hands-on experience. 18. Practice Zone: Chapter-wise practice sheets includes subjective questions for additional practice which are a part of each book.
Author: Marc Peter Deisenroth Publisher: Cambridge University Press ISBN: 1108569323 Category : Computers Languages : en Pages : 392
Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author: Joseph B. Wright
Author: Joseph B. Wright
Author: Joseph Wright
Author: Joseph B. Wright
Author: Joe Wright
Author: J.B. & Tutos I. Wright
Author: Joseph B. Wright
Author: Madhubun
Author: Marc Peter Deisenroth
Author: Joseph Bruce Wright
Author: Joseph Bruce Wright