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Mechanics of Materials I: Fundamentals of Stress & Strain and Axial Loading
Fractals and Scaling
Bacterial Genomes II: Accessing and Analysing Microbial Genome Data Using Artemis
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Learn to deploy a pre-trained BERT model for sentiment analysis as a REST API using FastAPI, PyTorch, and Hugging Face. Covers project setup, API creation, model integration, and real-time predictions.
Learn to build a sentiment classification model using BERT, Hugging Face, and PyTorch. Covers BERT basics, fine-tuning for sentiment analysis, model training, evaluation, and prediction from raw text.
Learn text preprocessing for sentiment analysis using BERT, Hugging Face, and PyTorch. Covers tokenization, padding, attention masks, dataset creation, and data splitting for NLP tasks.
Explore fundamental data visualization techniques using Matplotlib and Seaborn in Python. Learn to create histograms, box plots, violin plots, bar charts, line charts, scatter plots, and more for effective exploratory data analysis.
Learn to classify traffic signs using transfer learning with PyTorch. Explore data, build datasets, train a pre-trained ResNet model, evaluate performance, and make predictions on new images.
Learn to forecast Coronavirus cases using LSTM and PyTorch. Covers data preprocessing, model building, training, evaluation, and future predictions with real-world time series data.
Comprehensive guide to image processing with OpenCV in Python, covering essential techniques from basic operations to advanced manipulations for computer vision applications.
Learn essential Pandas operations for effective data analysis in Python, including handling missing values, manipulating columns, and basic plotting techniques.
Learn to build, train, and evaluate a neural network for weather prediction using PyTorch. Covers data preprocessing, model architecture, GPU acceleration, and practical applications.
Explore neural networks, perceptrons, and sigmoid neurons using TensorFlow.js. Learn about activation functions, network architecture, and weight initialization for machine learning in JavaScript.
Learn to build and train logistic regression models in TensorFlow.js for diabetes prediction. Covers data visualization, dataset creation, model evaluation, and advanced techniques.
Learn to fine-tune Falcon-7b LLM on a custom dataset using QLoRA. Covers model loading, LoRA adapter implementation, fine-tuning, progress monitoring, and performance evaluation on chatbot support FAQs.
Learn to run GPT4All, a free ChatGPT-like model, on Google Colab. Explore setup, prompts, and comparisons with ChatGPT in this hands-on tutorial.
Explore Stanford Alpaca's capabilities, learn inference techniques, and compare its performance to ChatGPT in this step-by-step tutorial on setting up and optimizing the model.
Learn to build a neural network for classification using PyTorch, covering data preparation, network structure, and implementation. Gain hands-on experience in deep learning fundamentals.
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