Session on "Use Cases and Risks of ML in Capital Markets" | 23rd Dec at 4pm Hi everyone! The AI and Risk Mitigation project is well underway and for the third session, we will be joined by Rachna Maheshwari, Associate Director at CRI… more
The 2023 Monsoon edition is curated by:
- Nischal HP, Vice President of Data Engineering and Data Science at Scoutbee. Nischal curated the MLOps conference which was held online between 23 and 27 July 2021.
- Sumod Mohan, Founder and CEO at AutoInfer. Sumod curated Anthill Inside 2019 edition, held in Bangalore on 23 November.
- AI and Research - covers research, findings, and solutions for challenges on building models in various areas such as fraud detection, forecasting, and analytics. This track delves into the latest methodologies for handling challenges such as large-scale data processing, distributed computing, and optimizing model performance.
- Industrial applications of ML - covers implementation of AI in the industry, with more focus on the AI models, the issues in training, gathering data so, and so forth. ML is being used at scale in industries such as automotive, mechanical, manufacturing, agriculture, and such domains. This track focuses on the challenges in this space, as we see innovation coming out of these industries in the pursuit of using ML on a second-to-second basis.
- AI and Product - covers strategies for building AI products to scale and mitigating challenges. This track provides insights on incorporating AI tools and forecasting techniques to improve model training, developing a working model architecture, and using data in the business context.
There are three phases in the lifecycle of an application - research, application and aftermath of the application.
- Assess capabilities, determining the new frontiers for AI.
- Find a use for the application.
- Learn how to run it, monitor it and update it with time.
The three tracks at the 2023 Monsoon edition of The Fifth Elephant will cover this lifecycle.
The Fifth Elephant 2023 Monsoon edition will be held in-person. Attendance is open to The Fifth Elephant members only. Purchase a membership to attend the conference in-person. If you have questions about participation, post a comment here.
- Data/MLOps engineers who want to learn about state-of-the-art tools and techniques, especially from domains such as automobile, agri-tech and mechanical industries.
- Data scientists who want a deeper understanding of model deployment/governance.
- Architects who are building ML workflows that scale.
- Tech founders who are building products that require AI or ML.
- Product managers, who want to learn about the process of building AI/ML products.
- Directors, VPs and senior tech leadership who are building AI/ML teams.
Sponsorship slots are open for:
- Infrastructure (GPU, CPU and cloud providers) and developer productivity tool makers who want to evangelise their offering to developers and decision-makers.
- Companies seeking tech branding among AI and ML developers.
- Venture Capital (VC) firms and investors who want to scan the landscape of innovations and innovators in AI and who want to source leads for investment in the AI and ML space.
Driving profitable growth with data and predictive modeling in startups.
By using advanced analytics and predictive modeling, growth systems have real-time access to customer journey insights. With this data and real time segmentation and prediction models, each stage of the marketing funnel can be optimized to more effectively nurture leads to convert. Which inturn helps drive up ROI.
Accurate channel attribution: Leverage probabilistic attribution to attribute conversions and revenue to specific marketing channels, enabling effective resource allocation and optimization of acquisition strategies.
Real-time user segmentation: Real time models to segment users based on acquisition channels, financial behavior, demographics, and preferences, facilitating personalized messaging and tailored experiences for different audience segments.
Predictive modeling for D1 ROI: Harness the power of predictive models to forecast the return on investment of newly acquired customers, leveraging historical data and advanced algorithms. This empowers data-informed decision-making on customer acquisition costs and retention strategies, optimizing long-term profitability.
Audience-specific proposition: Employ AI-driven analysis of customer data to gain insights into their unique needs and pain points, allowing for the customization of value propositions that address those specific requirements, setting the company apart from competitors.
Advanced analytics and predictive modeling gives companies more control over their marketing spends and revenues expected from the same, helping them to identify business opportunities and mitigate potential risks.
Author & Speaker:
Avinash Ramakanth, Sr. Vice President & Co-founder, Bright Money