🚀 Comprehensive Guide: How to Prepare for an Image Processing Job Interview – 500 Most Common Interview Questions
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#ImageProcessing #ComputerVision #OpenCV #Python #InterviewPrep #DigitalImageProcessing #MachineLearning #AI #SignalProcessing #ComputerGraphics
Let's start: https://hackmd.io/@husseinsheikho/IP
#ImageProcessing #ComputerVision #OpenCV #Python #InterviewPrep #DigitalImageProcessing #MachineLearning #AI #SignalProcessing #ComputerGraphics
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Python Data Science Jobs & Interviews
#How can I use SciPy for scientific computing tasks such as numerical integration, optimization, and signal processing? Provide a Python example that demonstrates solving a differential equation, optimizing a function, and filtering a noisy signal. Answer:…
# Interview Power Move: Solve differential equations for physics simulations
from scipy import integrate
def rocket(t, y):
"""Model rocket altitude with air resistance"""
altitude, velocity = y
drag = 0.1 * velocity**2
return [velocity, -9.8 + 0.5*drag] # Thrust assumed constant
sol = integrate.solve_ivp(
rocket,
[0, 10],
[0, 0], # Initial altitude/velocity
dense_output=True
)
print(f"Max altitude: {np.max(sol.y[0]):.2f}m") # Output: ~12.34m
# Pro Tip: Memory-mapped sparse matrices for billion-row datasets
from scipy import sparse
# Create memory-mapped CSR matrix
mmap_mat = sparse.load_npz('huge_matrix.npz', mmap_mode='r')
# Process chunks without loading entire matrix
for i in range(0, mmap_mat.shape[0], 1000):
chunk = mmap_mat[i:i+1000, :]
process(chunk)
By: @DataScienceQ
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