Advanced settings in Coze offer granular control over bot responses, with options for temperature adjustment and variable use for logic. GPT4 and GPT-4-turbo are also available. For FREE.
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Coze AI Platform Features and Workflow Capabilities
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Key features of Coze include a visual builder for bot workflows, allowing multiple bots to interact within a single chat environment. Similar to how the Mentions feature works on ChatGPT but within the context of a single bot
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Coze platform provides free access to AI bot building
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Coze stands out by letting users explore and build their own AI bots, without needing a subscription, making AI more accessible for FREE
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ByteDance Launches Coze AI Bot Platform
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It is not viral on AI Twitter but it should be ByteDance (a company behind @tiktok_us
) has launched Coze, an AI bot platform that directly competes with OpenAI's GPTs, enabling users to create and deploy custom AI bots. For FREE. -
Coze Platform Enables Custom AI Bot Deployment to Social Channels
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Unlike other platforms, Coze allows full bot customization and direct deployment to social platforms like @discord
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LangChain Deep Dive: LLMs, Agents, and Evaluations with Lance Martin
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GenAI solutions with LangChain: Lance Martin on LLMs, agents, evals, and more! Thanks to @neo4j for having our very own @RLanceMartin on their http://
GraphStuff.FM podcast! A great deep and technical dive into a lot of advanced topics! https://
graphstuff.fm/episodes/genai
-solutions-with-langchain-lance-martin-on-llms-agents-evals-and-more
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New platform for building and deploying AI assistants
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I am now testing a platform for building AI assistants which is 10 times better than what OpenAI offers. – GPT4-turbo access with granular tweaks
– AI assistants can be used in Telegram, Instagram, Discord, etc
– Loads of features in the builder UI Can you guess the name? -
Using LazyClassifier for Classification Problems
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Similarly here is using LazyClassifier for Classification Problems. Check this out:
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LazyRegressor: Streamline Model Selection for Regression Problems
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Model selection is key for any ML Project which includes identify the model that generalizes well and provides the best performance. This library can save time and effort by training and evaluating all your ML models at once. Here is using LazyRegressor for Regression Problems:
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Lazy Predict: Train and Evaluate All ML Models at Once
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Train and Evaluate all your Machine Learning Models at once! Introducing Lazy Predict a Python Library that allows you to train, test and evaluate all your ML models at once with just a few lines of code. Thread