KwickClips Artificial Intelligence

Artificial Intelligence: 197 short revision clips (page 3)

One idea per clip, with the answer written out underneath. Each clip links back to the full Artificial Intelligence lesson it came from.

Table: regression gives a number, classification gives a category.

Price of a used scooter?40 sec

Table of classification examples: email, payment, leaf photo and their labels.

What is the output of classification?39 sec

What does k mean in k-NN?39 sec

Rules for choosing k: too small, too large, odd k.

Is k = 1 risky?41 sec

Table of three nearest fruits to (5, 5) with distances and labels.

Which fruit wins with k = 3?40 sec

Table: labels given no, learning unsupervised, groups from data.

Can a computer find groups without labels?40 sec

Table of centroid positions for start, round 1 and round 2.

Where does a centroid move?39 sec

Elbow table: k 1 spread 5000, k 2 1200, k 3 900.

Which k does the elbow suggest here?40 sec

List of clustering uses: customer groups, news stories, bank payments.

How do shops use clustering?40 sec

Steps of splitting: try each question, check purity, keep the purest.

What is a pure group?37 sec

Table of decision tree strengths and weaknesses.

What is the catch with decision trees?39 sec

Table: greyscale 0 to 255, colour R G B values, photo as a grid of pixels.

What does a computer see in a photo?40 sec

Flow of vision steps: capture, clean, features, detect, understand.

What is the first step?37 sec

Table of computer vision uses: face unlock, medical scans, self-driving cars.

Is face unlock computer vision?41 sec

List of computer vision challenges: lighting, bias, privacy and deepfakes.

How does poor light affect vision AI?41 sec

Table of resolutions with pixel counts in lakh.

What does resolution count?39 sec

Table of pixel values: greyscale 0 to 255, RGB 3 values, yellow 255 255 0.

Why do pixel values stop at 255?40 sec

List of image features: edges, corners, blobs.

What is an edge?40 sec

Kernel 1, -1 on values 9, 9, 0 giving 0 on the left and 18 on the right.

What are the three steps?40 sec

Table of input counts for grey and colour 100 by 100 images.

How many inputs for a 100 x 100 grey image?38 sec

Table of CNN layers: convolution, pooling, flatten and their jobs.

What does pooling do?38 sec

Table: early layers edges, middle layers ears and eyes, deep layers cat face.

What does a CNN see first?41 sec

Code: imread, imshow, waitKey and resize to (400, 300).

Why did my resized photo stretch?41 sec

Code: imread, COLOR_BGR2GRAY and cvtColor.

Why turn photos grey first?41 sec

Code: imread grey, blur, Canny, imwrite edges.jpg.

What does the 0 in imread do?40 sec

Three reasons language is hard: many meanings, word order, sarcasm and mixing.

Why does 'He hit the bat' confuse a computer?44 sec

List of five NLP phases with what each checks.

Which phase checks grammar?43 sec

Table of NLP applications: translation, assistants, spam filter.

Is a spam filter NLP?40 sec

Table of AI domains and their data: numbers, images, text and speech.

What data does NLP use?43 sec

List of text normalisation steps in order.

What comes after sentence segmentation?46 sec

Table: studies to studi or study, caring to car or care.

What is the stem of 'studies'?42 sec

Bag of Words table with counts for three short documents.

What is the first step?38 sec

TF-IDF table: the scores 0, cricket scores 0.477 with N = 3.

Why does 'the' score zero?42 sec

Table comparing script bots and smart bots.

Does a script bot learn?43 sec

Python code for a keyword chatbot printing Hello!

What does get() do if the key is missing?39 sec

What are the three labels?41 sec

Limits of emotion AI: hidden sadness, cultural differences, consent.

Is an emotion AI result a fact?42 sec

Code: z = 1*0.7 + 1*(-0.9) + 0.1; print(1 if z > 0 else 0) outputs 0.

What does z come to?43 sec

Table of three layers: input, hidden, output and their jobs.

Why is the middle layer called hidden?40 sec

Learning loop: forward pass, compare, backpropagation.

What weights does a network start with?41 sec

Table: CNN images, RNN text and speech, GAN new images.

Which network creates new images?45 sec

Table: TensorFlow the engine, Keras the easy layer API.

Who makes TensorFlow?40 sec

Table: train 98 test 97 good; train 99 test 85 overfitting.

Train 99%, test 85%: what is it?40 sec

List of next steps: CNNs, Teachable Machine, Kaggle, LiteRT.

What improves image accuracy?41 sec

Points: creates new content, text images audio code, learns from huge data.

Can a computer draw a picture nobody drew before?41 sec

Steps: training finds patterns, stored as numbers, predicts next piece.

Does AI copy answers from the internet?39 sec

Table comparing discriminative and generative models with cat examples.

Which model says cat or dog?42 sec

Table of generative AI types with example tools and uses.

Which type makes voiceovers?44 sec

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Artificial Intelligence: 197 short revision clips (page 3)

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