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Build interactive data science and machine learning web apps in Python with Streamlit, from first app through deployment and multipage customization.
Learn essential workflows for creating and documenting data science projects in Google Colab, covering best practices for notebook organization and documentation in AI applications.
Build a hands-free LLM voice agent in Python with speech-to-text, text-to-speech, and conversation memory for natural verbal interactions.
Learn to prepare and clean bioactivity data for aromatase inhibitors using Python and RDKit, covering data loading, duplicate removal, and SMILES standardization for ML-ready datasets.
Master R programming fundamentals from setup to animated visualizations in this comprehensive 50-minute tutorial series.
Discover R programming fundamentals through hands-on tutorials covering environment setup, variables, file operations, and integration with Python and Google Colab.
Learn to build an end-to-end call center analytics workflow using Assembly AI and Python, covering transcription, speaker identification, sentiment analysis, and data visualization for extracting insights from conversations.
Explore the journey from academic bioinformatics to practical data app development, bridging theoretical knowledge with real-world applications in biological data analysis and visualization.
Learn to build a Python-based multilingual AI assistant that extracts audio, transcribes content, generates summaries, and synthesizes speech in 32 languages using AssemblyAI, Claude, and Eleven Labs.
Build an end-to-end data science project in R, from exploratory analysis and machine learning to interactive Shiny web applications.
Build interactive web applications in R with Shiny, including data-driven, machine learning, and health-monitoring examples, then deploy an app to Heroku.
Build a Python Streamlit app that transcribes YouTube audio and flags sensitive content with the AssemblyAI API.
Build a data science project with DagsHub, version code and data, track experiments, and compare model performance while exploring a new hypothesis.
Build a first machine learning model in Python with scikit-learn, comparing linear regression and random forest predictions on molecular solubility data.
Build a data science portfolio website with Hugo, customize its Markdown-based content and PaperMod theme, then deploy it through Hostinger.
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