Showing 2 open source projects for "oracle-apex-workflow"

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  • No-code email and landing page creation Icon
    No-code email and landing page creation

    Make campaign creation fast and easy with Knak

    Built for speed and collaboration, Knak streamlines campaign production with modular templates, real-time editing, simple collaboration, and seamless integrations with leading MAPs like Adobe Marketo Engage, Salesforce Marketing Cloud, Oracle Eloqua, and more. Whether you're supporting global teams or launching fast-turn campaigns, Knak helps you go from brief to build in minutes—not weeks. Say goodbye to bottlenecks and hello to marketing agility.
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  • A warehouse and inventory management software that scales with your business. Icon
    A warehouse and inventory management software that scales with your business.

    For leading 3PLs and high-volume brands searching for an advanced WMS

    Logiwa is a leader in cloud-native fulfillment technology, revolutionizing high-volume fulfillment for third-party logistics (3PLs), B2B and B2C fulfillment networks, and direct-to-consumer brands. Our flagship product, Logiwa IO, is an advanced Fulfillment Management System (FMS) designed to scale operations in the digital era. Logiwa elevates digital warehousing to new heights, ensuring dynamic and efficient fulfillment processes. Our commitment to AI-driven technology, combined with a focus on customer-centricity, equips businesses to adeptly navigate and excel in rapidly changing market landscapes. Discover the future of smart fulfillment and how you can fulfill brilliantly with Logiwa IO.
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  • 1
    Multi-Agent Orchestrator

    Multi-Agent Orchestrator

    Flexible and powerful framework for managing multiple AI agents

    Multi-Agent Orchestrator is an AI coordination framework that enables multiple intelligent agents to work together to complete complex, multi-step workflows.
    Downloads: 0 This Week
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  • 2
    ML for Trading

    ML for Trading

    Code for machine learning for algorithmic trading, 2nd edition

    On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms, how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news. ...
    Downloads: 1 This Week
    Last Update:
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