ChatGPT vs Google Bard

ChatGPT vs Google Bard: AI Language Models

What is the Difference Between Chat GPT and Google Bard? Artificial intelligence (AI) chatbots are being used by businesses to engage with clients, and certain language-based models have changed how people behave. Two examples of the powerful language-based strategies that have since altered the online world are Chat GPT and Google Bard. Testing is currently…

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ChatGPT Reinforcement Learning with Human Feedback

ChatGPT: Reinforcement Learning from Human Feedback

ChatGPT is a smart chatbot that is launched by OpenAI in November 2022. It is based on OpenAI’s GPT-3 family of large language models and is optimized using supervised and reinforcement learning approaches. Google launched a similar language application named Bard. Read ChatGPT vs. Bard. What is ChatGPT? ChatGPT is an abbreviation for Chat Generative…

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Create and Run Python Program Using PyCharm

Create and Run Python Program using PyCharm

A Python-specific Integrated Development Environment (IDE) called PyCharm offers a large range of crucial features for Python developers. Python programming can be done using the integrated development environment PyCharm. In addition to supporting Django web development, it offers code analysis, a graphical debugger, an integrated unit tester, integration with version control systems, and more. The…

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Why Naive Bayes Algorithm is NOT affected by Feature Scaling

Naive Bayes is a probabilistic algorithm that makes class predictions based on Bayes’ theorem, which states that the probability of a class given a set of features is proportional to the product of the probabilities of each feature given the class. The algorithm assumes independence between the features, so scaling the features should not affect…

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Exploration vs Exploitation in Reinforcement Learning

In Reinforcement Learning, exploration vs exploitation is a fundamental trade-off that agents must navigate to learn the optimal behavior in an environment. Exploration refers to the process of trying out new actions or visiting new states in order to gain more information about the environment and improve the agent’s understanding of the rewards and transition…

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