市場が追いついたら、もう遅い。
Feeling like the wonders of AI are going to take away my job Wait a minute to learn a different skill There is work to be done before that ・What jobs will be taken away by AI? ・What can't AI do? ・ What if you lose your job due to AI Are you worried about…
Epoch 1/100 83/83 [==============================] – 19s 164ms/step – loss: 0.0022 – mae: 0.0293 – acc: 3.7864e-04 Epoch 2/100 83/83 [==============================] – 14s 171ms/step – loss: 7.5855e-04 – mae: 0.0168 – acc: 3.7864e-04 Epoch 3/100 83/83 [==============================] – 15s 183ms/step – loss: 6.4637e-04 – mae: 0.0156 – acc: 3.7864e-04 Epoch 4/100 83/83 [==============================] – 15s 176ms/step…
[[[[53812.16322921 47536.67919788 46969.31610105 … 49303.581212651130.78025912 50699.04587463][52461.86132487 46316.94964869 45754.99439207 … 48042.9550292849858.05759064 49399.9161135 ][53062.94169324 46876.60686311 46323.43441121 … 48638.8470875250462.71647981 49990.95768209]… [52198.23675318 46112.62220043 45564.72720465 … 47845.5604277449660.86049885 49179.83784084][52511.93986297 46359.93881913 45827.42514543 … 48112.912666349887.74522474 49497.74288834][52998.36303047 46804.74537743 46238.56459162 … 48573.3205507650380.7481082 49940.35874819]] [[50217.26949623 51898.16071222 49460.02154144 … 44440.3100794847931.02711719 48350.4105729 ][48924.19446068 50575.25789205 48198.96722111 … 43297.0210512446679.32017406 47071.7169633 ][49555.99899699 51188.25025889 48808.69806119 … 43847.600518147267.47690235 47719.54756853]… [48713.59805041 50350.03251488 48027.04418418 ……
Defined $I={1,2,…,N}$ is the set of goods. When the weight of each item $i in I$ is $w_i$ value and the upper limit of the total weight of $ v_i$ item is $W$, the following is called the knapsack problem. $$max ∑{i in I}v_iw_i s.t. ∑{i in I}v_iw_ile Wxin mathbb{N}(forall in I)$$ where $x_i$ represents…
Defined $I={1,2,…,N}$ is the set of goods. When the weight of each item $i in I$ is $w_i$ value and the upper limit of the total weight of $ v_i$ item is $W$, the following is called the knapsack problem. $$max ∑{i in I}v_iw_i s.t. ∑{i in I}v_iw_ile Wxin mathbb{N}(forall in I)$$ where $x_i$ represents…
Defined $I={1,2,…,N}$ is the set of goods. When the weight of each item $i in I$ is $w_i$ value and the upper limit of the total weight of $ v_i$ item is $W$, the following is called the knapsack problem. $$max ∑{i in I}v_iw_i s.t. ∑{i in I}v_iw_ile Wxin mathbb{N}(forall in I)$$ where $x_i$ represents…
Learn with books 1. Deep Learning (Adaptive Computation and Machine Learning series) This deep learning book is a resource for people involved in machine learning, by people involved in machine learning, to start from scratch for getting involved in machine learning. Provided by Ian Goodfellow, Yoshua Bengio, Aaron Courville What you will learn Configuration Part…
Learn with books 1. Deep Learning (Adaptive Computation and Machine Learning series) This deep learning book is a resource for people involved in machine learning, by people involved in machine learning, to start from scratch for getting involved in machine learning. Provided by Ian Goodfellow, Yoshua Bengio, Aaron Courville What you will learn Configuration Part…
$$QFT |x> = frac{1}{2^{n/2}} sum_{y=0}^{2^n-1} e^{2 pi iyx / 2^n} |y>$$ $|x_1>$ = -H-CR2-CR3-.. -CRn—————–$|x_2>$ = ——————H-CR2–.. ———-.. $|x_{n-1}>$ = ———————.. –H-CR2—$|x_n>$ = ————————-.. ——–H-
Perceptron Source code Learn more about perceptrons Import. Create data. Plot. Encode the discriminating function $$y(x) = f(w^T phi (x))$$ Code the activation function $$f(a) =begin{cases}+1 (a geq 0) \-1 (a leq 0)end{cases}$$ Predict. Code parameter updates $$w^{i+1} = w^{i} + eta phi (n) t(n)$$ Learn. Least squares Source code Learn more about least squares…