Modules The main modules of functionality that make up LangChain, consisting of: – Prompt Templates
– LLMs
– Utilities (search, vector DBs, etc)
– Chains
– Agents
– Memory
TOOLS
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LangChain Core Modules: Prompts, LLMs, Chains, Agents
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LangChain Revamps Documentation with New Sections
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New Year, New Docs In an effort to make LangChain easier-to-use than ever before, we've revamped our docs. Sections include: Getting Started
Modules
[NEW] Use Cases
[NEW] Ecosystem
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Plotly and Bokeh: Essential Data Visualization Libraries
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Great addition Sarah! @plotly and @bokeh is amazing
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Weekly Writing Resources: How-tos, Deconstructions, Tactics, and AI Prompts
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2,035+ writers write better/faster/stronger when they sign up for: • 1 Big how-to or story/lesson
• 1 Writing deconstruction
• 1 Tactic I use all the time
• 1 Genius AI writing prompt
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Abacus AI Simplifies ML Deployment with End-to-End Solutions
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The average machine learning engineer spends 98% of their time stitching services together. At @abacusai
, we take data from you, train a model, deploy it and give you an endpoint you can use immediately. Less complexity → More time to focus on what truly matters. -
Keras: High-Level Neural Network Library Built on TensorFlow
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6. Keras Keras is a high-level library for building and training neural networks. It is built on top of TensorFlow and provides a simple and intuitive interface for defining and training models. It is well-suited for quick prototyping. https://
keras.io -
TensorFlow: Google’s Open-Source Machine Learning Platform
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5. TensorFlow TensorFlow is an open-source machine-learning library developed by Google. It provides a flexible and efficient platform for building, training, and deploying machine learning models, including support for deep learning. https://
tensorflow.org -
PyTorch: Facebook’s Open-Source Deep Learning Framework
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4. PyTorch PyTorch is an open-source machine-learning library developed by Facebook. It is a popular choice for deep learning and provides support for dynamic computation graphs, which allow for more flexible and efficient model design. https://
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scikit-learn: comprehensive machine learning library for Python
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3. scikit-learn scikit-learn is a library for machine learning in Python. It provides a wide range of algorithms for classification, regression, clustering, and model selection, as well as tools for evaluating the performance of these models. https://
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Pandas: Essential Data Manipulation Library for Analysis
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2. Pandas Pandas is a library for data manipulation and analysis. It provides functions and data structures for efficiently working with large datasets, including support for handling missing data, time series analysis, and merging and joining data. https://
pandas.pydata.org