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Lecture 12 - Exercises 2-3
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
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Implementation of NN and lecture 9 autoencoder
Avatar Matteo Gioele Collu
Matteo Gioele Collu
Avatar Matteo Gioele Collu
Matteo Gioele Collu
 0
Lecture 8 - Sigmoid function derivative
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
 0
Lect 12 - Preprocess data using Titanic dataset
Avatar LUIGI BORRIELLO
LUIGI BORRIELLO
Avatar LUIGI BORRIELLO
LUIGI BORRIELLO
 0
Exercise lecture 12 - Encoding range-type variables
Avatar JUAN BAEZA RUIZ-HENESTROSA
JUAN BAEZA RUIZ-HENESTROSA
Avatar JUAN BAEZA RUIZ-HENESTROSA
JUAN BAEZA RUIZ-HENESTROSA
 0
LECT12 - Preprocessing Titanic dataset
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
 0
Lecture 7 - Perceptron implementation
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
 0
Lecture 7 - Weight initialization
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
 0
Lecture 7 - Multilayer perceptron for boolean formulas
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
 0
Preprocessing - SVM - Naive Bayes - Logistic Regression
Avatar AMIR SADEGHI
AMIR SADEGHI
Avatar AMIR SADEGHI
AMIR SADEGHI
 0
Perceptron as dot products: kernelized perceptron
Avatar LORENZO D'ANTONI
LORENZO D'ANTONI
Avatar LORENZO D'ANTONI
LORENZO D'ANTONI
 0
Lecture 12 - Titanic KNN
Avatar MARIJA NENADIĆ
MARIJA NENADIĆ
Avatar MARIJA NENADIĆ
MARIJA NENADIĆ
 0
Lecture 12 - Titanic Dataset
Avatar Salvatore Gatto
Salvatore Gatto
Avatar Salvatore Gatto
Salvatore Gatto
 0
Lecture 12 Exercise 3
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 0
Lecture 12 Exercise 2
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 0
Lecture07-Learning Algorithm
Avatar Nicolò Predenz
Nicolò Predenz
Avatar Nicolò Predenz
Nicolò Predenz
 0
Lecture 6 - ID3 vs CART
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
Avatar NIKOLA ANDRIĆ MITROVIĆ
NIKOLA ANDRIĆ MITROVIĆ
 0
Neural Netwrok Implementation
Avatar SOLMAZ MOHAMMADI
SOLMAZ MOHAMMADI
Avatar SOLMAZ MOHAMMADI
SOLMAZ MOHAMMADI
 0
Lecture 12 - Churn data set
Avatar Nikola Bulat
Nikola Bulat
Avatar Nikola Bulat
Nikola Bulat
 0
L09 - Implementation of the Network on slide 15
Avatar Salvatore Gatto
Salvatore Gatto
Avatar Salvatore Gatto
Salvatore Gatto
 0
L12 - Titanic Dataset
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
 0
Lec-12 Preprocessing Titanic Dataset
Avatar Riccardo Cappi
Riccardo Cappi
Avatar Riccardo Cappi
Riccardo Cappi
 0
L09- Backpropagation
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
 0
Boston houses price prediction using Ridge Regression
Avatar MARCO ANDREA LIMONGELLI
MARCO ANDREA LIMONGELLI
Avatar MARCO ANDREA LIMONGELLI
MARCO ANDREA LIMONGELLI
 0
Lec9 Exercise
Avatar MOHAMMADREZA REZAEI FEYZABADY
MOHAMMADREZA REZAEI FEYZABADY
Avatar MOHAMMADREZA REZAEI FEYZABADY
MOHAMMADREZA REZAEI FEYZABADY
 0
Derivation of backpropagation for multiple hidden layers
Avatar FILIPPO FANTINATO
FILIPPO FANTINATO
Avatar FILIPPO FANTINATO
FILIPPO FANTINATO
 0
LECT05-ID3 on boolean formulas explained
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
 0
Lecture 8: Implement the Delta rule optimization
Avatar LORENZO D'ANTONI
LORENZO D'ANTONI
Avatar LORENZO D'ANTONI
LORENZO D'ANTONI
 0
Lecture 8: Derivative of the Sigmoid function
Avatar LORENZO D'ANTONI
LORENZO D'ANTONI
Avatar LORENZO D'ANTONI
LORENZO D'ANTONI
 0
Perceptron (with the delta rule)
Avatar SOLMAZ MOHAMMADI
SOLMAZ MOHAMMADI
Avatar SOLMAZ MOHAMMADI
SOLMAZ MOHAMMADI
 0
Lecture 9 - Implement the network given on Slide 15.
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
 0
Lecture 8-Delta rule optimization & prove of sigma formula
Avatar Mahshad Golafshan
Mahshad Golafshan
Avatar Mahshad Golafshan
Mahshad Golafshan
 0
Lecture 9: NN with one hidden layer
Avatar DENNIS RODERMUND
DENNIS RODERMUND
Avatar DENNIS RODERMUND
DENNIS RODERMUND
 0
Lecture 8: Delta Rule optimization
Avatar DENNIS RODERMUND
DENNIS RODERMUND
Avatar DENNIS RODERMUND
DENNIS RODERMUND
 0
Lecture 7 Perceptron Algorithm
Avatar DENNIS RODERMUND
DENNIS RODERMUND
Avatar DENNIS RODERMUND
DENNIS RODERMUND
 0
VC-Dimension of Perceptron
Avatar Moones Mobaraki
Moones Mobaraki
Avatar Moones Mobaraki
Moones Mobaraki
 0
L07 - Perceptron
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
 0
Lecture 03 Ex 2
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 1
Possible error Lecture 9 - NN3 slide 9/17
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
Avatar Riccardo Cappi
Riccardo Cappi
 3
Lecture 8 Exercise 1
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 0
Lec 07 Coefficient η
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 0
Lecture 06
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 0
Lecture 9: Back-Propagation python implementation
Avatar Riccardo Cappi
Riccardo Cappi
Avatar Riccardo Cappi
Riccardo Cappi
 0
LECT07 - Implementation of perceptron algorithm
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
 0
Lecture 4 - VC-Dimension of other hypothesis spaces, e.g. intervals in R
Avatar HOU CHENG LAM
HOU CHENG LAM
Avatar HOU CHENG LAM
HOU CHENG LAM
 0
Python implementation of percepetrons to calculate some boolean functions
Avatar MARCO ANDREA LIMONGELLI
MARCO ANDREA LIMONGELLI
Avatar MARCO ANDREA LIMONGELLI
MARCO ANDREA LIMONGELLI
 0
Lecture 7 - Implementation of Perceptron
Avatar DAVIDE BASSAN
DAVIDE BASSAN
Avatar DAVIDE BASSAN
DAVIDE BASSAN
 0
L9Ex2 - Hidden Layer Representation
Avatar FILIPPO FANTINATO
FILIPPO FANTINATO
Avatar FILIPPO FANTINATO
FILIPPO FANTINATO
 0
Lecture 8: Delta Rule python implementation
Avatar Riccardo Cappi
Riccardo Cappi
Avatar Riccardo Cappi
Riccardo Cappi
 0
lecture 5
Avatar AHMAD KARAMI
AHMAD KARAMI
Avatar AHMAD KARAMI
AHMAD KARAMI
 0
Lec 8 Exercises
Avatar AMIR SADEGHI
AMIR SADEGHI
Avatar AMIR SADEGHI
AMIR SADEGHI
 0
Lec7 Exercises
Avatar AMIR SADEGHI
AMIR SADEGHI
Avatar AMIR SADEGHI
AMIR SADEGHI
 0
Lecture 8 - exercise
Avatar MARIJA NENADIĆ
MARIJA NENADIĆ
Avatar MARIJA NENADIĆ
MARIJA NENADIĆ
 0
Lec8-Excersies
Avatar MOHAMMADREZA REZAEI FEYZABADY
MOHAMMADREZA REZAEI FEYZABADY
Avatar MOHAMMADREZA REZAEI FEYZABADY
MOHAMMADREZA REZAEI FEYZABADY
 0
Lec7- Exercises
Avatar MOHAMMADREZA REZAEI FEYZABADY
MOHAMMADREZA REZAEI FEYZABADY
Avatar MOHAMMADREZA REZAEI FEYZABADY
MOHAMMADREZA REZAEI FEYZABADY
 0
October exercises
Avatar DAMIANO MASON
DAMIANO MASON
Avatar DAMIANO MASON
DAMIANO MASON
 0
Create a Decision Tree with ID3: exercise on paper
Avatar DANIELE TRENTIN
DANIELE TRENTIN
Avatar DANIELE TRENTIN
DANIELE TRENTIN
 0
L03 - Ridge regression
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
Avatar CRISTIANO PANIGHEL
CRISTIANO PANIGHEL
 0
Lecture 7 exercise
Avatar SANJAR TLEPIN
SANJAR TLEPIN
Avatar SANJAR TLEPIN
SANJAR TLEPIN
 0
Build a decision tree "by hand"
Avatar STEFANO SORGENTE
STEFANO SORGENTE
Avatar STEFANO SORGENTE
STEFANO SORGENTE
 0
Decision Tree exercise by Python
Avatar STEFANO SORGENTE
STEFANO SORGENTE
Avatar STEFANO SORGENTE
STEFANO SORGENTE
 0
Logical Operations and Perceptron Implementation (Complete version of pervious code)
Avatar Moones Mobaraki
Moones Mobaraki
Avatar Moones Mobaraki
Moones Mobaraki
 0
Lecture 8 - Exercises
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
 0
LECT07 - XOR gate
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
Avatar DAVIDE VEZZARO
DAVIDE VEZZARO
 0
Lecture 8
Avatar Shakiba Farjood Fashalami
Shakiba Farjood Fashalami
Avatar Shakiba Farjood Fashalami
Shakiba Farjood Fashalami
 0
Lecture 7 - Exercises 1 and 3
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
Avatar ALESSANDRO RESTA
ALESSANDRO RESTA
 0
Lecture 7: Implementation of the Perceptron algorithm
Avatar ANDREA FAVERO
ANDREA FAVERO
Avatar ANDREA FAVERO
ANDREA FAVERO
 0
1-layer NN in python with gradient descent
Avatar Matteo Gioele Collu
Matteo Gioele Collu
Avatar Matteo Gioele Collu
Matteo Gioele Collu
 0
Lecture 08 - Sigmoid derivative proof
Avatar Nikola Bulat
Nikola Bulat
Avatar Nikola Bulat
Nikola Bulat
 0
Lecture 6 - CART vs ID3
Avatar LUIGI BORRIELLO
LUIGI BORRIELLO
Avatar LUIGI BORRIELLO
LUIGI BORRIELLO
 0
Lesson 8 - Implementation of Delta Rule
Avatar Salvatore Gatto
Salvatore Gatto
Avatar Salvatore Gatto
Salvatore Gatto
 0
Lecture 5 exercise
Avatar SANJAR TLEPIN
SANJAR TLEPIN
Avatar SANJAR TLEPIN
SANJAR TLEPIN
 0
lecture 08
Avatar Sahar Sheikhi
Sahar Sheikhi
Avatar Sahar Sheikhi
Sahar Sheikhi
 0
Lecture 7 - Perceptron
Avatar SAMUELE POZZEBON
SAMUELE POZZEBON
Avatar SAMUELE POZZEBON
SAMUELE POZZEBON
 0
Lecture 8 - Gradient descent implementation
Avatar SAMUELE POZZEBON
SAMUELE POZZEBON
Avatar SAMUELE POZZEBON
SAMUELE POZZEBON
 0
Lecture7_Perceptron
Avatar TAHA ENAYAT
TAHA ENAYAT
Avatar TAHA ENAYAT
TAHA ENAYAT
 0
Lecture5
Avatar TAHA ENAYAT
TAHA ENAYAT
Avatar TAHA ENAYAT
TAHA ENAYAT
 0
Lecture4
Avatar TAHA ENAYAT
TAHA ENAYAT
Avatar TAHA ENAYAT
TAHA ENAYAT
 0
Lecture 08_NN-Exercise
Avatar Hannane Habibi
Hannane Habibi
Avatar Hannane Habibi
Hannane Habibi
 0
Lecture 8, Neural Networks Exercise
Avatar NILA AKBARI
NILA AKBARI
Avatar NILA AKBARI
NILA AKBARI
 0
lecture 04, VC dimension
Avatar Hannane Habibi
Hannane Habibi
Avatar Hannane Habibi
Hannane Habibi
 0
Lecture 4, VC-Dimension of intervals
Avatar NILA AKBARI
NILA AKBARI
Avatar NILA AKBARI
NILA AKBARI
 0
Lesson 8 - Proof of the derivative of sigmoid function
Avatar Salvatore Gatto
Salvatore Gatto
Avatar Salvatore Gatto
Salvatore Gatto
 0
Lecture 07 Perceptron
Avatar Hannane Habibi
Hannane Habibi
Avatar Hannane Habibi
Hannane Habibi
 0
Lecture 7, Perceptron Implementation
Avatar NILA AKBARI
NILA AKBARI
Avatar NILA AKBARI
NILA AKBARI
 0
VC-Dimension of other hypothesis spaces
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
 0
Lecture 05 ID3
Avatar Hannane Habibi
Hannane Habibi
Avatar Hannane Habibi
Hannane Habibi
 0
Lecture 5 Boolean formulas ID3
Avatar NILA AKBARI
NILA AKBARI
Avatar NILA AKBARI
NILA AKBARI
 0
Show that σ′(y) = σ(y)(1 − σ(y))
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
 0
Lecture 7 NOT implementation
Avatar ANDREA FAVERO
ANDREA FAVERO
Avatar ANDREA FAVERO
ANDREA FAVERO
 1
Lecture 07 (ANN)
Avatar Sahar Sheikhi
Sahar Sheikhi
Avatar Sahar Sheikhi
Sahar Sheikhi
 0
lecture7
Avatar Mahshad Golafshan
Mahshad Golafshan
Avatar Mahshad Golafshan
Mahshad Golafshan
 0
Lecture3Q1
Avatar TAHA ENAYAT
TAHA ENAYAT
Avatar TAHA ENAYAT
TAHA ENAYAT
 0
Derivation of the sigmoid function: σ′(y) = σ(y)(1 − σ(y))
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
Avatar AVA LOUISE FINNEGAN
AVA LOUISE FINNEGAN
 0
Lecture 4 exercise
Avatar SANJAR TLEPIN
SANJAR TLEPIN
Avatar SANJAR TLEPIN
SANJAR TLEPIN
 0
Activity lecture 5
Avatar JANARDHAN JAYACHANDRA KAMMATH
JANARDHAN JAYACHANDRA KAMMATH
Avatar JANARDHAN JAYACHANDRA KAMMATH
JANARDHAN JAYACHANDRA KAMMATH
 0
lecture 05 DTs
Avatar Sahar Sheikhi
Sahar Sheikhi
Avatar Sahar Sheikhi
Sahar Sheikhi
 0
Linear Regression - from theory to code
Avatar SEPASEH HAKIMINEJAD
SEPASEH HAKIMINEJAD
Avatar SEPASEH HAKIMINEJAD
SEPASEH HAKIMINEJAD
 0
Lecture 07 - Perceptron boolean functions
Avatar Nikola Bulat
Nikola Bulat
Avatar Nikola Bulat
Nikola Bulat
 0
Proof for sigmoid differential equation
Avatar MARVIN JOHANNES HEIDINGER
MARVIN JOHANNES HEIDINGER
Avatar MARVIN JOHANNES HEIDINGER
MARVIN JOHANNES HEIDINGER
 0