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21. Post Trade Clearing, Settlement & Processing
MIT OpenCourseWare
10. Financial System Challenges & Opportunities
MIT OpenCourseWare
7. Technical Challenges
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3. Blockchain Basics & Cryptography
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19. Primary Markets, ICOs & Venture Capital, Part 1
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1. Introduction for 15.S12 Blockchain and Money, Fall 2018
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Chalk Radio, A Podcast about Inspired Teaching at MIT (Teaser)
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Nuclear Gets Personal with Prof. Michael Short (S1:E1)
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How Africa Has Been Made to Mean with Prof. Amah Edoh (S1:E2)
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Making Deep Learning Human with Prof. Gilbert Strang (S1:E3)
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Social Impact at Scale, One Project at a Time with Dr. Anjali Sastry (S1:E4)
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Film is for Everyone with Prof. David Thorburn (S1:E5)
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Lecture 12: Aircraft Performance
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Lecture 3: Learning to Fly
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Lecture 13: Interpreting Weather Data
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Lecture 21: Weather Minimums and Final Tips
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Hand-on, Minds On with Dr. Christopher Terman (S1:E6)
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Part 4: Eigenvalues and Eigenvectors
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Part 5: Singular Values and Singular Vectors
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Part 3: Orthogonal Vectors
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Part 2: The Big Picture of Linear Algebra
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Part 1: The Column Space of a Matrix
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Intro: A New Way to Start Linear Algebra
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9. Chromatin Remodeling and Splicing
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28. Visualizing Life - Fluorescent Proteins
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20. Roth's theorem III: polynomial method and arithmetic regularity
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8. Szemerรฉdi's graph regularity lemma III: further applications
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19. Roth's theorem II: Fourier analytic proof in the integers
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12. Pseudorandom graphs II: second eigenvalue
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1. A bridge between graph theory and additive combinatorics
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Special Episode: Teaching Remotely During Covid-19 with Prof. Justin Reich
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Spring 2020 Update from Dean Rajagopal
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S1E7: Unpacking Misconceptions about Language & Identities with Prof. Michel DeGraff
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Climate 101 Live
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Welcome for Volunteers (for EarthDNA's Climate 101)
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Learning to Fly with Drs. Philip Greenspun & Tina Srivastava (S1:E8)
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Thinking Like an Economist with Prof. Jonathan Gruber (S1:E9)
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2. Cyber Network Data Processing; AI Data Architecture
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1. Artificial Intelligence and Machine Learning
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2: Resistor Capacitor Circuit and Nernst Potential - Intro to Neural Computation
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14: Rate Models and Perceptrons - Intro to Neural Computation
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4: Hodgkin-Huxley Model Part 1 - Intro to Neural Computation
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18: Recurrent Networks - Intro to Neural Computation
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3: Resistor Capacitor Neuron Model - Intro to Neural Computation
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15: Matrix Operations - Intro to Neural Computation
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13: Spectral Analysis Part 3 - Intro to Neural Computation
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16: Basis Sets - Intro to Neural Computation
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20: Hopfield Networks - Intro to Neural Computation
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8: Spike Trains - Intro to Neural Computation
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7: Synapses - Intro to Neural Computation
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19: Neural Integrators - Intro to Neural Computation
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5: Hodgkin-Huxley Model Part 2 - Intro to Neural Computation
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6: Dendrites - Intro to Neural Computation
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17: Principal Components Analysis_ - Intro to Neural Computation
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12: Spectral Analysis Part 2 - Intro to Neural Computation
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11: Spectral Analysis Part 1 - Intro to Neural Computation
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9: Receptive Fields - Intro to Neural Computation
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10: Time Series - Intro to Neural Computation
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1: Course Overview and Ionic Currents - Intro to Neural Computation
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The Power of OER with Profs. Mary Rowe and Elizabeth Siler (S1:E10)
MIT OpenCourseWare
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