Learn Logistic Regression for Machine Learning vs Linear Regression – Chapter 1

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Learn Logistic Regression for Machine Learning vs Linear Regression - Chapter 1

May 9, 2019|Rohit Ghosh

Rohit Ghosh is a graduate of IIT-Bombay with over 5 years of experience as a data scientist. Rohit started his professional life working as a risk analyst at Nomura. It’s here that he discovered his love for machine learning and decided to pivot into data science. After re-training as a data scientist, Rohit had a successful run working for ListUp and Data Science Labs. Post this stint, he decided to apply his data science skills to fix healthcare challenges. Thus, his first startup Qure.ai was born. Qure.ai is a healthcare startup that leverages deep learning in radiology image processing. In addition to growing his startup, Rohit is also keen on learning about cryptocurrencies and reinforcement learning – an emerging niche in machine learning.  

Key takeaways for you

  • Why Logistic over Linear Regression?
  • Decision boundary
  • Hyperparameter tuning
  • Cost Function
  • Gradient Descent
  • Evaluating matrix
  • Precision and recall
  • Logarithmic loss

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