cd0361_advanced-computer-vision-and-deep-learning

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

dl_pytorch

Code for the Deep Learning with PyTorch lesson

keywordrecognitionbasedchatbot

A Lord of the Rings: The Fellowship of the Ring chatbot

lda_mixed_groups

Case Study 1.1.2: Finding Themes in Project Descriptions Instructor: Tamara Broderick Activity Type: Optional Case Study Description: Using Latent Dirichlet Allocation to discover topics in a corpus of text. Finding Themes in Project Descriptions - LDA Analysis. Self-Help Documentation: In this document, we walk through some tips to help you with doing your own analysis on MIT EECS faculty data using stochastic variational inference on LDA. We provide some examples for the following programming environment: Python. Download Self-Help Documentation Time Required: The time required to do this activity varies depending on your experience in the required programming background. We suggest planning somewhere between 1 & 3 hours. Remember, this is an optional activity for participants looking for hands-on experience. Have questions? Feel free to discuss this case study with other participants in the Discussion Forum under Module 1 - Case Studies Section.

mesa

Mesa is an agent-based modeling framework in Python

neural-localization

Train an RL agent to localize actively (PyTorch)

p3_implement_slam

Landmark Detection and Tracking (SLAM) project for CVND

processingtextpart1

English grammar theory

pytorchtutorial

PyTorch Tutorials from my YouTube channel

sentiment_analysis_model_twitter

sergiocanov

stockmarket_dashboard

testing-git