Numpy - Linear Combination

Linear Combination by Numpy

Linear Regression via Linear Combination in Numpy

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Reference
Linear and Non-linear Regression

Basic Code

def linear_forward_loop(W, B, X):
    result = []
    for i in range(len(W)):  # for each neural
        y = 0
        for j in range(len(X)):  # for input dimension
            y += W[i][j] * X[j]
        y += B[i]
        result.append(y)
    return np.array(result)

# Broadcasting

def linear_forward_basic(W, B, X):
    result = []
    for row in W:
        y = np.sum(row * X)  # linear combination for each neural
        result.append(y)
    return np.array(result) + B

# np.dot
def linear_forward(W, B, X):
    return np.dot(W, X) + B