• Psychology 1

    PREVIOUS: Learning Seeing, hearing, tasting, feeling.. Learning requires us acquire knowledge about the world. So how do we know the world? Nativism believed that it was just in us–knowledge was given to us by God. Empiricism suggested we acquire knowledge through experience and are the reflection on our experiences. Synthesis...

  • Psychology 1

    PREVIOUS: Biological Bases of Mind and Behavior Standard Deviation & how it relates to Normal Distribution. Within 1 std dev, you have 68% of people, 2 95%, 3 99%. NEXT: Learning

  • Psychology 1

    PREVIOUS: Methods and Statistics Our mind generally learns like this: We pick up information through our senses,form internal representations of what that information means, reflect on that knowledge, which guides our behavior. Afterwards, we communicate that knowledge to others. A traditionalist view of learning and association involves only external stimuli,...

  • Psychology 1

    PREVIOUS: Introduction to Psychology Neurons Everything psychological is biological. Your brain releases chemicals when you’re scared or happy or whatever. All of your sensations, feelings, mind are all tied to your brain and the neurons. Like organisms, these sort of have a hierarchical structure: Cell :: Neurons Tissue :: Nerves,...

  • Psychology 1

    PREVIOUS: Table of Contents What is Psychology? Psychology delves into the realm of dreams and consciousness and the human mind. Up until the 1900s, it was defined as “the study of the soul” (Greek). Questions to consider when diving into this subject: How can humans commit genocide? Torture? How do...

  • Psychology 1

    BACK: Classes Preface This is going to be a mix between Crash Course Psychology (thanks Hank Green), and my online PSYCH W1 class that I worked stupid hard to register for. Textbook: Introduction to Psychology by James Kalat Intro to Psychology–History, Origins, Scope Biological Bases of Mind and Behavior Methods...

  • Unsupervised Learning

    BACK: Trees, Random Forests UNDER HEAVY CONSTRUCTION: NOT EVERYTHING MAY BE CORRECT. unsupervised learning Table of Contents

  • Support Vector Machine

    BACK: Trees, Random Forests UNDER HEAVY CONSTRUCTION: NOT EVERYTHING MAY BE CORRECT. unsupervised learning NEXT: Unsupervised Learning