Splitwise is a free tool for friends and roommates to track bills and other shared expenses, so that everyone gets paid back. On the web, iPhone, and Android!
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Which is more popular?
Based on our record, PyTorch
seems to be more popular. It has been mentioned
146 times
since March 2021.
social mentions
0 vs 146
Personal Finance popularity
100% vs 0%
alternatives listed
240+ vs 151
Base details
Website, pricing, platforms and company facts side by side.
User-Friendly Interface Splitwise provides an intuitive and easy-to-navigate interface, making it straightforward for users to add expenses, keep track of debts, and settle up.
Multi-Platform Availability Available on the web, iOS, and Android, Splitwise ensures users can access and manage their expenses from almost any device.
Expense Tracking The app allows users to easily log and categorize expenses, which can be particularly useful for group trips, shared households, or any shared financial responsibility.
Flexible Split Options Users can split expenses equally, by percentages, shares, or custom amounts, providing flexibility in how costs are divided among group members.
Currency Conversion Splitwise supports multiple currencies, which is handy for international travel or groups with members from different countries.
Bill Reminders The app sends reminders for outstanding balances, helping users to stay on top of their payments and avoid forgotten debts.
Integration with Payment Platforms Splitwise can integrate with payment platforms like PayPal and Venmo for easy settlement of balances.
Possible disadvantages
Privacy Concerns Since Splitwise involves sharing financial information with others, there could be privacy concerns for those unwilling to share detailed expense data.
Subscription-Based Features Some advanced features, such as expense exporting and additional integrations, require a Splitwise Pro subscription.
Manual Entry Requirement Splitwise requires users to manually enter expenses, which could be time-consuming and prone to errors if not done diligently.
Limited Automatic Reconciliation While Splitwise helps track who owes whom, it does not automatically reconcile or pay off balances, leaving users responsible for manual payment.
Dependency on Group Honesty The accuracy of the expense records relies on the honesty and diligence of all group members, which may not always be reliable.
Potential for Confusion The various options for splitting bills (equally, by shares, etc.) can sometimes lead to confusion or disputes among users over what is fair.
Dynamic Computation Graph PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
Pythonic Nature PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
Strong Community Support PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
Flexibility and Control PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
Support for GPU Acceleration PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
Rich Ecosystem PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.
Possible disadvantages
Limited Production Deployment Tools PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
Lesser Adoption in Industry While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
Inconsistent API Changes As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
Steeper Learning Curve for Beginners Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
Less Mature Documentation Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.
Analysis
An editorial look at what each product does well and who it suits.
SplitwisePyTorch
Overall verdict
Splitwise is a highly effective tool for managing shared expenses, especially if frequent splitting of costs is involved. Its features make it easy to track who owes what, and its automatic calculations save time and reduce errors.
Why this product is good
Splitwise is popular because it simplifies sharing and tracking expenses among groups, making it ideal for roommates, friends on trips, or any group spendings.
It automatically calculates balances and reminds users about payments, reducing the awkwardness of asking others for money.
Offers a user-friendly interface both on web and mobile apps, which makes managing expenses convenient and accessible.
Supports multiple currencies, which is great for international travel groups.
Integration with payment platforms like PayPal and Venmo for easy settlement of debts.
Recommended for
Roommates who need to regularly split household bills and expenses.
Groups of friends or families who often travel together and need to manage shared travel costs.
Colleagues or classmates working on projects or events that require shared funding.
Anyone who wants to avoid the hassle of manually tracking and settling shared expenses.
Overall verdict
Yes, PyTorch is considered a good deep learning framework.
Why this product is good
Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.
Recommended for
Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.
Splitwise is among the most commonly used group payment apps that can easily keep a systematic record of all your informal debts including restaurant bills, travel expenses, cost of accommodation, and much more. With...
Splitwise employs an intelligent algorithm to calculate the exact amount owed by each user. It shows who paid for what, how much amount was paid by each member, and any outstanding balances. Furthermore, the...
For example, shared items like appetizers would be split among the entire group or just a few people in the group. The app can handily accommodate large parties by allowing you to add up to 10 people to each group....
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement...
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural...
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for...
Recommendations tracked on public social media and blogs since March 2021.
Splitwise0 mentionsPyTorch146 mentions
Tracking Splitwise since Mar 2021.
Train a Modern VLM on One GPU: Qwen3-VL with Unsloth and Transformers 5.12.1
Install PyTorch first with the selector on pytorch.org, then install the Python packages used by the examples:.
- Source: dev.to
/
4 days ago
Context Encoders: Learning to Inpaint and What It Teaches a Network
In this technical blog, we will deep dive into the core of context encoders and implement it using PyTorch and CelebA dataset from scratch.
- Source: dev.to
/
28 days ago
Developer Take On: A High-Resolution Neural Cellular Automata
PyTorch: A popular deep learning framework for Python.
- Source: dev.to
/
5 months ago
TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Tricount
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