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Dasturlash Pythonda Sun'iy Intellekt

Uzbek → English Level B175 cards3 stories

Pythonda kodlash va sun'iy intellektni o'rganish uchun o'z lug'atingizni yarating! Kod tuzilishi, kutubxonalar va yangi texnologiya yutuqlari haqida gaplashishni o'rganing, shu bilan birga dasturlash ko'nikmalaringizni takomillashtiring. Texnologiya mavzularini yaxshiroq muhokama qilishni istaydigan o'rta darajali o'rganuvchilar uchun mukammal.

Dasturlash Pythonda Sun'iy Intellekt

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 They used an outdated library, so she had to implement a new one.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

  • kod yozish to write code
  • U har kuni kod yozadi. She writes code every day.
  • U o'z loyihalari uchun kod yozadimi? Does he write code for his projects?
  • Ular Pythonda kod yozishmaydi. They do not write code in Python.
  • dasturni tuzatish to debug a program
  • Dasturni tuzatdingizmi? Have you debugged the program yet?
  • Dastur hali tuzatilmagan. The program hasn't been debugged yet.
  • kutubxonadan foydalanish to use a library
  • Python kutubxonasidan foydalanish to use a Python library
  • Ushbu Python kutubxonasini loyihamiz uchun ishlata olamizmi? May we use this Python library for our project?
  • Sizning jamoangiz eskirgan kutubxonadan foydalanishi mumkin emas. Your team may not use that outdated library.
  • modelni o'qitish to train a model
  • Olimlar AI modellarini katta ma'lumotlar to'plami bilan o'qitadi. Scientists train AI models with large datasets.
  • Model o'qitildimi? Has the model been trained yet?
  • algoritmni optimallashtirish to optimize an algorithm
  • algoritmni optimallashtirish to optimize the algorithm
  • U algoritmni optimallashtirganliklarini aytdi. He said they had optimized the algorithm.
  • Murakkab bo'lishiga qaramay, algoritm tez optimallashtirildi. Despite being complex, the algorithm was optimized quickly.
  • xususiyatni amalga oshirish to implement a feature
  • Biz xususiyatlarni qo'lda amalga oshirar edik. We used to implement features manually.

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