Python · Theory

Grid search

Theory

103/268

Grid search

Grid search is a specialised library. Say what job it does in one line, then one tiny call you would write. Don’t fake a full ML pipeline on a fresher page.

Grid search: PyTorch = tensors/models. OpenCV = images. SimpleImputer = fill missing numbers. Folium = maps. Spark/MLlib = big data. nsetools = market quotes. Grid search = try hyper-parameters. scraping = fetch HTML then parse.

Viva for Grid search — purpose + one function name + one caution (API keys, missing values, robots.txt).

Output — best k 3. Grid search tries each setting and keeps the best score.

Exam tip

What it does + one API name + one caution.

Example

# Grid search
best, best_s = None, -1
for k in (3, 5, 7):
    score = 1 / k
    if score > best_s:
        best, best_s = k, score
print("best k", best)

Output: best k 3. Grid search tries each setting and keeps the best score.

Short notes

DefGrid search — one job, one library.
RuleGrid search — purpose + one call.
TrapGrid search — copying a huge notebook without explaining one line.

Python · Theory

Grid search

← All stacks

Theory

103/268

Grid search

Grid search is a specialised library. Say what job it does in one line, then one tiny call you would write. Don’t fake a full ML pipeline on a fresher page.

Viva for Grid search — purpose + one function name + one caution (API keys, missing values, robots.txt).

Output — best k 3. Grid search tries each setting and keeps the best score.

Exam tip

What it does + one API name + one caution.

Example

# Grid search
best, best_s = None, -1
for k in (3, 5, 7):
    score = 1 / k
    if score > best_s:
        best, best_s = k, score
print("best k", best)

Output: best k 3. Grid search tries each setting and keeps the best score.

Short notes

DefGrid search — one job, one library.
RuleGrid search — purpose + one call.
TrapGrid search — copying a huge notebook without explaining one line.

Grid search

Example

Short notes

Questions

Grid search

Example

Short notes

Questions