Day 87 Fast: Debugging AI Models – Fix Any Bug in Minutes

The day every AI engineer needs: the complete debugging toolkit. We break your Day 85 app with real bugs (vanishing gradients, memory leaks, dead layers) — then fix them in seconds using TensorBoard, the 7-step system, and pro tricks.
Tomorrow Day 88: real-world AI projects!

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1970s jazz, morning coffee, Python, TensorFlow, deploy model, Streamlit, FastAPI, Hugging Face Spaces, TensorFlow Serving, model deployment, AI web app, DailyAIWizard, computer vision, NLP, sentiment analysis, image classification

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Transcript

00:00TensorBoard is your MRI for neural nets. See gradients, weights, activations live.

00:06I found a dead layer in 30 seconds. Would have taken days without it.

00:12Log everything, loss, accuracy, weights, gradients.

00:16I'll add callbacks and show you a dying gradient live.

00:21GradCam shows exactly where your model is looking. Is it the cat or the carpet?

00:25My model was predicting cat because of the carpet.

00:30GradCam caught it instantly.

00:32Essential for computer vision debugging.

00:35I'll run GradCAM on your day 85 image model live.

00:40Tef data bugs are silent. Wrong shuffling. No prefetch caching disasters.

00:46I trained for 12 hours because prefetch was off. Data starvation.

00:52Always inspect your pipeline with .as underscore numpy underscore iterator.

00:56I'll show a broken pipeline fix with prefetch and cache.

01:02One command shows if your model is built wrong. Input, output shapes, param count.

01:07I once had a model with zero parameters. Summary. Caught it.

01:12Always run model.summary after building.

01:15I'll break the day 85 model shape live. Then fix it.

01:20Add asserts to catch impossible values. Nan, negative probabilities, wrong shapes.

01:26I once had negative probabilities. Assert. Saved me.

01:32Fail fast. Fail loud.

01:34I'll add asserts to day 85. Watch them scream when I break it.

01:40Weights and biases logs everything. Compare 50 runs in one click.

01:45I found my best model from three weeks ago. Wand B remembered.

01:50Free tier is amazing.

01:53I'll log your day 85 training live.

01:55Your training is slow. Profiler shows exactly where. Data, GPU, CPU.

02:03I was blaming the model. It was tf.data the whole time.

02:09Built into TensorBoard.

02:12I'll profile your day 85 app live.

02:15Shapp tells you exactly which words made it positive or negative.

02:20My model hated the word but. Shapp showed me.

02:24Explainable AI gold standard.

02:28I'll explain a wrong prediction live.

02:31Write tests for your pre-processing, model output, predictions.

02:36Never break silently again.

02:38I added tests after a disaster.

02:41Never going back.

02:44CI slash CD for AI.

02:47I'll write five tests for day 85 app live.

02:49Automatically validate every new batch.

02:53Catch corrupted data before training.

02:56I once trained on all NAN images.

02:59Great expectations would have saved me.

03:02Data tests are as important as code tests.

03:06I'll add three expectations live.

03:09Your complete debugging checklist.

03:12Print it, save it, live by it.

03:13I have this taped above my monitor.

03:16Saved me hundreds of hours.

03:19This plus TensorBoard plus the seven steps equals unstoppable.

03:24Download link in description.

03:26Free forever.

03:29Every single one of us has lost days to these bugs.

03:32Now you're immune.

03:34I still have the Slack message where I cried for six hours straight.

03:38This is what separates juniors from seniors.

03:43You're now in the 1% who actually debug fast.

Day 87 Fast: Debugging AI Models – Fix Any Bug in Minutes | #DailyAIWizard

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