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Comprehensive tutorial on Python regular expressions, covering essential concepts, methods, and advanced techniques for efficient text pattern matching and manipulation.
Create five classic games in Python, enhancing coding skills while building an impressive portfolio. Perfect for beginners seeking hands-on practice with popular game logic and implementations.
Learn to create an efficient Python development environment using Docker, covering volumes, Docker Compose, container debugging, and IDE integration for streamlined workflow and improved productivity.
Learn to build a media library and content analysis dashboard using Python and Cloudinary, covering image uploading, tagging, searching, and creating an interactive gallery and dashboard.
Learn Supabase for Python: overview, setup, CRUD operations, authentication, security, policies, storage, and functions. Hands-on tutorial for building scalable backends quickly.
Create a Python fitness app that sends daily workout emails using HarperDB, covering setup, development, and deployment in a hands-on tutorial.
Learn to build a Python app that converts speech to text and integrates with Notion API for efficient note-taking, enhancing productivity and organization skills.
Learn to build and integrate a custom chatbot into a website using Python, Flask, and JavaScript in this hands-on project. Gain practical skills in AI development and web integration.
Comprehensive introduction to HuggingFace and Transformers library, covering sentiment analysis, Model Hub exploration, and fine-tuning techniques for NLP tasks.
Learn MongoDB with Python: setup, PyMongo usage, and essential operations for inserting, updating, deleting, and finding documents in this comprehensive crash course.
Comprehensive introduction to TensorFlow 2.0 and Keras, covering key concepts and practical applications in deep learning through hands-on projects and real-world examples.
Master essential NumPy functions for efficient array operations, data manipulation, and numerical computing in Python. Covers basics to advanced topics like multidimensional arrays, broadcasting, and linear algebra.
Learn to implement Autoencoders in PyTorch, covering theory, data loading, simple and CNN architectures, training loops, and image plotting. Gain practical deep learning skills through hands-on coding.
Learn to predict time sequences using PyTorch and LSTMs. Create sine waves, build an LSTM model, implement a training loop, and perform final testing for accurate forecasting.
Comprehensive PyTorch tutorial covering fundamentals, advanced concepts, and practical implementations for deep learning, from tensor basics to CNNs and transfer learning.
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