文章分类 - machine learning
AI
摘要：Goals In this lab, you will: extend the previous linear and logistic cost functions with a regularization term. rerun the previous example of over-fit
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摘要：regularize linear Regression how to certify which values are needed to be regularize? $$ simpler\ model\ less\ likely\ to\ overfit\ \ J(\vec{w},b)=\fr
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摘要：import copy, math import numpy as np %matplotlib widget import matplotlib.pyplot as plt from lab_utils_common import dlc, plot_data, plt_tumor_data, s
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摘要：training gradient descent we should know that the loss function also has the only global minimum, so we can use the same method to get the proper $\ve
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摘要：Cost function for logistic regression how to choose and b? squared error cost $J(\vec{w},b)=\frac{1}{m} \sum^{m}{i=1}\f
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摘要：classification when the y can only be one of two values:"binary classification" class = category false:0 true: 1 one example of binary classification:
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摘要：Feature scaling Feature and parameter values when
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摘要：import copy, math import numpy as np import matplotlib.pyplot as plt plt.style.use('./deeplearning.mplstyle') np.set_printoptions(precision=2) # reduc
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摘要：Multiple linear regression When the situation involve multiple features, we use $$ \begin{align*}\label{2} &x_j = j^{th} feature\ &n = number \ of\ fe
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摘要：import numpy as np # it is an unofficial standard to use np for numpy import time # NumPy routines which allocate memory and fill arrays with value a
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摘要：gradient descent import math, copy import numpy as np import matplotlib.pyplot as plt plt.style.use('./deeplearning.mplstyle') from lab_utils_uni impo
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摘要：Gradiant descent **Have some function J(w,b), want ** Outline: Start with some w,b (set w =0, b =0) Keep ch
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摘要：python cost function import numpy as np %matplotlib widget import matplotlib.pyplot as plt from lab_utils_uni import plt_intuition, plt_stationary, pl
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摘要：Cost function example cost funtion definition: linear regression function: $$ \widehat{y}^{(i)}=f_{w,b}(x^{i})\ f_{w,b}(x^{(i)}) = wx^{(i)}+b\ Cost \
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摘要：import numpy as np #NumPy, a popular library for scientific computing import matplotlib.pyplot as plt #Matplotlib, a popular library for plotting data
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摘要：Linear regression model regression model predicts numbers supervised learning model data has "right answers" Classification model predicts catogories
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摘要：supervised learning vs unsupervised learning supervised learing input output labelX ————————> YLearns from being given "right answers" this is the exa
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