best way to install/integrate numpy scikit to an existing zeppelin install on sandbox Labels: Apache Spark azeltov Guru Created 03-08-2016 02:25 PM Hello Experts! I noticed that the default zeppelin install on hdp sandbox does not come with numpy and scikit learn packages...
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I try to make dense vector for 'feature' directly with numpy array. x_flatten = x_train.reshape((800,-1)) z_train = np.empty((800, 224*224*3)) for i in range(800): z_train[i,:] = x_flatten[i,:] df = pd.DataFrame(columns=['feature','label']) for i in range(799):...
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import numpy as np from scipy.optimize import minimize def rosen(x): return sum(100.0 * (x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0) x0 = np.array([1.3, 0.7, 0.8, 1.9, 1.2]) res = minimize(rosen, x0, method='nelder-mead') print(res.x) Least Squares We ...
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Unlike NumPy that immediately performs the computation and produces the result, tensorflow only gives us a handle (of type Tensor) to a node in the graph that represents the result. If we try printing the value of z directly, we get something like this: Tensor("MatMul:0", shape=(10, 10...