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#Install package import sys !{sys.executable} -m pip install numpy !{sys.executable} -m pip install matplotlib # import packages import numpy as np import scipy from scipy import optimize from scipy.optimize import minimize Deterministic model Time scale: the decisions are taken every hour during the day.

Project Logistic regression #Install package import sys !{sys.executable} -m pip install numpy !{sys.executable} -m pip install matplotlib !{sys.executable} -m pip install scikit-learn import numpy as np import matplotlib.pyplot as plt from time import time import random import sklearn 1) Device Type: Choose a device type (Lights, Camera, Smart Speaker, Thermostat,…) and plot the data

Gradient descent and quadratic penalization Continuous optimization — ENT 305 We study the projection of $(0,1)$ onto the line $x=y$: $$\min_{(x,y)\in\mathbb R^2} f(x,y)=\frac12\bigl[x^2+(y-1)^2\bigr],\qquad h(x,y)=y-x=0.$$ import numpy as np import matplotlib.pyplot as plt 1.

TP1 #Install package import sys !{sys.executable} -m pip install numpy !{sys.executable} -m pip install matplotlib # import packages import numpy as np import scipy.sparse as sp import scipy.sparse.linalg as spla import matplotlib.

TP 4 Logistic regression import sys !{sys.executable} -m pip install numdifftools !{sys.executable} -m pip install scikit-learn import numpy as np import matplotlib.pyplot as plt from time import time import random #params = {'tex.

#Install package import sys !{sys.executable} -m pip install numpy !{sys.executable} -m pip install matplotlib # import packages import numpy as np import scipy from scipy import optimize from scipy.optimize import minimize Deterministic model Time scale: the decisions are taken every hour during the day.

Gradient descent vs Newton To find the infimum of an arbitrary cost function, we use here the gradient descent. Let us consider the function $f(x,y)=2x^2+y^2-xy+2$ that we aim at minimizing on $ \mathbb{R}^2$.

TP2: Kolmogorov #Install package import sys !{sys.executable} -m pip install numpy !{sys.executable} -m pip install matplotlib # import packages import numpy as np import matplotlib.pyplot as plt ============================================================ TP Kolmogorov Goal : Show that for $u(x,\mu)=tanh(\frac{x-\mu}{\delta}).

#Install package import sys !{sys.executable} -m pip install numpy !{sys.executable} -m pip install matplotlib # import packages import numpy as np import scipy from scipy import optimize from scipy.optimize import minimize Deterministic model Time scale: the decisions are taken every hour during the day.