Exploring Data Wrangler in VS Code - Python Data Science
Discover Data Wrangler in VS Code: Efficiently explore, analyze, and clean Airbnb listings data. Learn to invoke and use this powerful tool for streamlined data preprocessing in Python notebooks.
How ML-Powered Data Cleaning Streamlines the AI Pipeline
Explore ML-powered data cleaning techniques to streamline AI pipelines, automate labor-intensive tasks, and overcome impediments in data preparation for efficient data science workflows.
How to Create Data-Cleaning Auto-Pipelines With Python
Develop automated data cleaning pipelines using Scikit-Learn to streamline data processing, reduce time spent on preprocessing, and enhance reproducibility in your data science projects.
Exploring Datasets with Python and Pandas
Explore datasets using Python and pandas. Learn essential data analysis techniques for scientists, engineers, and analysts working with diverse datasets.
Fraud Detection Using OpenShift Data Science - A Step-by-Step Guide
Detect fraudulent transactions using AI/ML on OpenShift Data Science. Learn the workflow, partner solutions, and step-by-step implementation for financial institutions.
Best Practice From Julia - Impact Through Efficient Research Code
Explore Julia's impact on efficient research code, from self-driving cars to astronomy. Learn about cutting-edge tools for mathematical modeling and machine learning in various fields.
Animating in Blender With AI
Experience a week-long journey of AI-assisted animation in Blender, from 3D scanning to VR performance capture, culminating in a unique and entertaining final animation.
Predict Giant Pumpkin Weights With Tidymodels Workflowsets
Learn to predict giant pumpkin weights using tidymodels workflowsets. Explore data visualization, modeling techniques, and parallel processing for efficient analysis of #TidyTuesday pumpkin competition data.
Python for AI: Exploring and Cleaning Data with Pandas
Learn to explore, clean, and prepare data for machine learning using Pandas. Covers handling missing values, outliers, categorical data, and feature preparation for model training.
Scraping ArXiv Papers with OpenAI's GPT 3.5 - AI Assistant
Learn to build an AI research assistant that scrapes ArXiv papers using GPT-3.5, transforming messy references into a clean format for efficient information extraction and graph-based paper organization.
Economic Data Analysis Project with Python Pandas - Data Scraping, Cleaning and Exploration
Learn to analyze economic data using Python and Pandas. Scrape, clean, and explore indicators with the FRED API. Create insightful visualizations and comparisons for unemployment and participation rates.
Big Query Live Training - A Deep Dive Into Data Pipelining
Explore data pipelining with BigQuery: learn to process, analyze, and visualize large datasets efficiently. Gain hands-on experience in extracting, loading, and transforming data for marketing insights.
Get Your Data Production Ready Fast with Ruby Polars
Discover how Ruby Polars can efficiently clean and prepare large datasets, expediting data import processes for applications and AI/ML projects using basic operations.
Building Machine Learning Systems for the Era of Data-Centric AI
Explore the evolution of ML systems beyond model training, focusing on data quality, trustworthiness, and regulatory compliance through systematic data debugging and cleaning approaches.
Leveraging Large Language Models for ETL, Analytics, and Modern Data Stack
Discover how Large Language Models revolutionize data workflows, from ETL processes to analytics automation, with practical insights on implementation challenges and production deployment strategies.
Automate Stocks and Crypto Research with Python and Deep Learning - Full Python Project
Learn to automate stock and crypto research using Python, web scraping, and deep learning. Build a pipeline to gather, summarize, and analyze financial news for various assets.
Real-World Python Machine Learning Tutorial With Scikit Learn
Comprehensive Python machine learning tutorial covering sentiment analysis using scikit-learn, from data preparation to model evaluation and optimization, with practical examples using Amazon reviews.
Semantic Search for AI - Testing Out Qdrant Neural Search
Explore semantic search implementation using Qdrant, covering Docker setup, data cleaning, microservice creation, and leveraging sentence embeddings for improved AI-powered search capabilities.
Neural Nets for NLP 2017 - Adversarial Learning
Explore adversarial learning in NLP, covering generative adversarial networks, feature vs. output adversaries, discrete outputs, and applications to language tasks.
Topic Modeling Workshop for Beginners in Python
Learn topic modeling in Python using Gensim, spaCy, and NLTK. Covers data preparation, exploratory analysis, tokenization, LDA modeling, and evaluation techniques for beginners.
Project Walkthrough - AskFSDL - LLM Bootcamp
Walkthrough of building an LLM-powered Discord bot for answering questions about neural network applications, covering tooling, data cleaning, infrastructure, frontend, embeddings, and monitoring.