Software Alternatives, Accelerators & Startups

Daily Time Tracking VS PyTorch

Compare Daily Time Tracking VS PyTorch and see what are their differences

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Daily Time Tracking logo Daily Time Tracking

Daily shows what you have been working on and for how long. It creates accurate timesheets by asking what you are doing, so no more timers or switching tasks. Use its data to submit your hours, create invoices or simply increase your productivity.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Daily Time Tracking Landing page
    Landing page //
    2020-10-30

Daily is a 5 star-rated time tracker for Mac that works by asking what you are working on. It provides a better way to track your daily activities without the hassle of toggling timers, switching tasks or taking notes. Use its accurate timesheets to submit your hours, create better invoices not missing any work or simply increase your productivity.

Underneath Daily’s user-friendly interface supporting both light and dark mode, you will find dozens of useful features. Examples include synchronisation via iCloud, automation using AppleScript, exporting to CSV, JSON and more, a tracking scheduler and system-wide keyboard shortcuts.

Try Daily for free by downloading it from the Mac App Store and join thousands of other employees, freelancers, founders and professionals.

  • PyTorch Landing page
    Landing page //
    2023-07-15

Daily Time Tracking features and specs

  • User-Friendly Interface
    Daily Time Tracking offers a simple and intuitive interface making it easy for users to navigate and log their time.
  • Detailed Reporting
    The platform provides comprehensive reporting features that allow users to analyze their productivity and time allocation.
  • Cross-Platform Compatibility
    It supports multiple platforms including web, iOS, and Android, enabling users to track time on the go.
  • Integration with Other Tools
    Daily Time Tracking integrates with popular productivity tools such as Asana, Trello, and Slack, enhancing its utility.
  • Customizable Settings
    Users can customize settings to suit their specific workflow requirements, including creating custom task categories and labels.

Possible disadvantages of Daily Time Tracking

  • Subscription Costs
    The platform requires a subscription, which may be a barrier for individual users or small teams with limited budgets.
  • Learning Curve
    Despite its user-friendly design, there is still a learning curve for users who are not familiar with time-tracking tools.
  • Limited Offline Functionality
    The app requires an internet connection for most features, which can be limiting in areas with poor connectivity.
  • Potential for Overhead
    Constantly logging time can become an administrative overhead, detracting from actual productive work.
  • Data Security Concerns
    Storing time-tracking data on a third-party service may raise concerns about data privacy and security for some users.

PyTorch features and specs

  • 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 of PyTorch

  • 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.

Daily Time Tracking videos

Daily Time Tracking

PyTorch videos

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Daily Time Tracking and PyTorch)
Productivity
100 100%
0% 0
Data Science And Machine Learning
Time Tracking
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Daily Time Tracking and PyTorch

Daily Time Tracking Reviews

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PyTorch Reviews

10 Python Libraries for Computer Vision
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 tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
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 language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
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 computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...

Social recommendations and mentions

Based on our record, PyTorch should be more popular than Daily Time Tracking. It has been mentiond 133 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Daily Time Tracking mentions (56)

  • Time Tracking
    Check out Daily if you don't like manually toggling timers. Instead, it periodically asks what you are doing. Source: almost 2 years ago
  • "Blind" Time-tracker idea
    Just for an app reference, a quick google reference I found this https://dailytimetracking.com not sure if this helps, but seems pretty simple and not intrusive/invasive. Source: almost 2 years ago
  • Add work log for another user via API
    I'm the developer behind a time-tracking app, and I'm looking to build a Zapier integration for a larger customer who uses Jira. They want tracked time to automatically be pushed to Jira using their work log capability. They want to avoid using a (way more expensive) organization plan of Zapier, though. Source: almost 2 years ago
  • Looking for a good time tracking app with lots of statistics and graphs
    If you're on a Mac, you might want to try out DailyTry out Daily if you're on a Mac. Although it focuses more on simplicity, you might like its way of tracking time: by periodically asking what you are doing. For other options, check out this blog post. Source: about 2 years ago
  • Time tracker free
    Not free, unfortunately, but check out Daily. It tracks time by periodically asking what you are doing instead of requiring you to toggle timers when you switch tasks. Alternatively, check out this blog post for other options. Source: about 2 years ago
View more

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 8 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 21 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 1 month ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing Daily Time Tracking and PyTorch, you can also consider the following products

Zoom - Equip your team with tools designed to collaborate, connect, and engage with teammates and customers, no matter where you’re located, all in one platform.

TensorFlow - 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.

GoToMeeting - GoToMeeting is a web conferencing service offering a range of services which are available on Mac, PC, iOS and Android devices.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

join.me - Instant screen sharing. Instant Aha!

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.