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4 Unique Methods to Optimize your Python Code for Data Science

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Overview Writing optimized Python code is a crucial piece in your data science skillset Here are four methods to optimize your Python code (with. The post 4 Unique Methods to Optimize your Python Code for Data Science appeared first on Analytics Vidhya.

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The Future of Agriculture: Leveraging Data Science to Optimize Crop Yield

Analytics Vidhya

In the past, agriculture was done manually, with farmers relying on experience and suspicion to decide when and how to set […] The post The Future of Agriculture: Leveraging Data Science to Optimize Crop Yield appeared first on Analytics Vidhya.

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Optimization Essentials for Machine Learning

Analytics Vidhya

Where is Optimization used in DS/ML/DL? The post Optimization Essentials for Machine Learning appeared first on Analytics Vidhya. What are Convex […]. What are Convex […].

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Optimize your optimizations using Optuna

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Optuna is a state-of-the-art automatic hyperparameter tuning framework that is completely written in Python. The post Optimize your optimizations using Optuna appeared first on Analytics Vidhya.

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Data Science Fails: Building AI You Can Trust

The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. The optimal level of disclosure to AI stakeholders.

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ML Hyperparameter Optimization App using Streamlit

Analytics Vidhya

This article was published as a part of the Data Science Blogathon About Streamlit Streamlit is an open-source Python library that assists developers in creating interactive graphical user interfaces for their systems. It was designed especially for Machine Learning and Data Scientist team. Frontend […].

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AWS Storage: Cost Optimization Principles

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Data is the most crucial aspect contributing to the business’s success. Organizations are collecting data at an alarming pace to analyze and derive insights for business enhancements.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Register today to save your seat!