Construeix el teu vocabulari per programar en Python i explorar la intel·ligència artificial! Aprèn a parlar sobre l'estructura del codi, les llibreries i els nous avenços tecnològics mentre millores les teves habilitats de programació. Perfecte per a estudiants d'nivell intermedi que volen parlar sobre temes tecnològics amb més fluïdesa.
Stories
Lena Optimizes Python Algorithm
English
Lena loves writing code in Python. She has been working on an AI project for a large company, but her algorithm hasn't been optimized yet. "Have you debugged the program yet?" her team asked last week. She said she had processed the datasets efficiently, but the model still needed work. Despite being complex, the project was not impossible. They used an outdated library, so she had to implement a new one. "May we train the models quickly?" she asked. The scientists confirmed they could. Every day, she writes code to analyze data and improve features. He used to debug manually, but now they automate the process. Your project? It might be next!
Neural Network Improves Over Time
English
The scientists were excited about their new neural network. They had built it last month to automate repetitive tasks, but the initial results weren’t accurate. "Have you preprocessed the data correctly?" she asked. He admitted the dataset wasn’t analyzed properly before training. Despite their difficulties, they decided to refactor the old code. "We must fine-tune the parameters," he said. They integrated new APIs and deployed the model on the server. Even though errors crashed the program at first, it now handles them gracefully. The results are better this week. "Were the tasks automated yet?" she wondered. Next, they will visualize the data to improve accuracy.
Model Training Challenges
English
The team was excited—they had just trained a new classifier. The data had been split into training and test sets, and the features were encoded manually. Despite their efforts, the model was overfit. "Have you evaluated the performance yet?" asked the lead engineer. She confirmed the results were incomplete. "We must normalize the data," she said. They scaled the variables, but the model still underfit. "May we try regularization?" someone suggested. By morning, the model had been reevaluated. The normalization improved accuracy, but the performance was not high enough. "Your dataset might be too small," he warned. "Has the model been loaded successfully?" They visualized the results and found a mistake—some features had not been scaled properly. "Did you check the encoding?" she asked. The team used to encode data automatically, but now they did it manually. Despite the challenges, they were determined to improve the model. "We must train it again," she said. The classifier has been working since yesterday, but the results have not improved yet. "Have you tried adjusting the hyperparameters?" he asked. The team knew they had to be patient—good models take time.
Sample flashcards 20
escriure codi→to write code
Escriu codi cada dia.→She writes code every day.
Escriu codi pels seus projectes?→Does he write code for his projects?
No escriuen codi en Python.→They do not write code in Python.
depurar un programa→to debug a program
Has depurat el programa encara?→Have you debugged the program yet?
El programa encara no s'ha depurat.→The program hasn't been debugged yet.
utilitzar una biblioteca→to use a library
utilitzar una biblioteca de Python→to use a Python library
Podem utilitzar aquesta biblioteca de Python per al nostre projecte?→May we use this Python library for our project?
El vostre equip no pot utilitzar aquesta biblioteca desactualitzada.→Your team may not use that outdated library.
entrenar un model→to train a model
Els científics entrenen models d'IA amb grans conjunts de dades.→Scientists train AI models with large datasets.
S'ha entrenat el model encara?→Has the model been trained yet?
optimitzar un algorisme→to optimize an algorithm
optimitzar l'algorisme→to optimize the algorithm
Va dir que havien optimitzat l'algorisme.→He said they had optimized the algorithm.
Tot i ser complex, l'algorisme es va optimitzar ràpidament.→Despite being complex, the algorithm was optimized quickly.
implementar una funció→to implement a feature
Solíem implementar funcions manualment.→We used to implement features manually.
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