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Exist VS TensorFlow

Compare Exist VS TensorFlow and see what are their differences

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Contents:
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  3. » Reviews
  4. » Alternatives

Exist logo Exist

Track everything in one place, understand your life.

TensorFlow logo 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.
  • Exist Landing page
    Landing page //
    2022-07-19
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Exist features and specs

  • Comprehensive Data Integration
    Exist integrates data from various services such as fitness trackers, social media, sleep monitors, and more, allowing for a wide range of data collection and analysis.
  • Personal Insights
    It provides personalized insights and correlations based on the data collected, helping users to better understand their habits and improve their lifestyle.
  • Custom Tracking
    Users can create custom tags to track specific activities or behaviors that are important to them, offering a high degree of personalization.
  • API Access
    Exist offers an API, enabling users to create custom integrations and extend the platform's functionality.
  • Mobile App Availability
    Exist is available as a mobile app, making it easy for users to input and check their data on the go.

Possible disadvantages of Exist

  • Subscription Cost
    Exist requires a paid subscription after the initial trial period, which may be a barrier for some users.
  • Privacy Concerns
    Collecting and integrating a wide range of personal data can raise privacy concerns, especially if the service is ever compromised.
  • Data Overload
    The sheer amount of data available can be overwhelming for some users, making it challenging to identify the most relevant insights.
  • Learning Curve
    New users may face a learning curve as they try to navigate the platform and make the best use of its features.
  • Limited Free Features
    The free version offers limited functionality, which may not be sufficient for users looking to fully explore the platform before committing to a subscription.

TensorFlow features and specs

  • Comprehensive Ecosystem
    TensorFlow offers a complete ecosystem for end-to-end machine learning, covering everything from data preprocessing, model building, training, and deployment to production.
  • Community and Support
    TensorFlow boasts a large and active community, as well as extensive documentation and tutorials, making it easier for beginners to learn and experts to get help.
  • Flexibility
    TensorFlow supports a wide range of platforms such as CPUs, GPUs, TPUs, mobile devices, and embedded systems, providing flexibility depending on the user's needs.
  • Integrations
    TensorFlow integrates well with other Google products and services, including Google Cloud, facilitating seamless deployment and scaling.
  • Versatility
    TensorFlow can be used for a wide range of applications from simple neural networks to more complex projects, including deep learning and artificial intelligence research.

Possible disadvantages of TensorFlow

  • Complexity
    TensorFlow can be challenging to learn due to its complexity and the steep learning curve, particularly for beginners.
  • Performance Overhead
    Although TensorFlow is powerful, it can sometimes exhibit performance overhead compared to other, lighter frameworks, leading to longer training times.
  • Verbose Syntax
    The code in TensorFlow tends to be more verbose and less intuitive, which can make writing and debugging code more cumbersome relative to other frameworks like PyTorch.
  • Compatibility Issues
    Frequent updates and changes can lead to compatibility issues, requiring significant effort to keep libraries and dependencies up to date.
  • Mobile Deployment
    While TensorFlow supports mobile deployment, it is less optimized for mobile platforms compared to some other specialized frameworks, leading to potential performance drawbacks.

Exist videos

+ Add

Exist - Board Game Review

More videos:

  • Review - Exist Review
  • Review - Daiwa Exist Spinning Reel [Review & Unboxing]

TensorFlow videos

+ Add

What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

More videos:

  • Tutorial - TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka
  • Review - TensorFlow in 5 Minutes (tutorial)

Category Popularity

0-100% (relative to Exist and TensorFlow)

Exist

TensorFlow

Habit Building
100 100%
Habit Building
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Productivity
100 100%
Productivity
0% 0
AI
0 0%
AI
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 Exist and TensorFlow

Exist Reviews

We have no reviews of Exist yet.
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TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...
Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, Exist should be more popular than TensorFlow. It has been mentiond 43 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.

Exist mentions (43)

  • Apple courier may have stolen 2 MacBooks, () Apple is not going to help
    As someone who has been on and off the Degoogle train (I ran full LineageOS without Google Play at one point) and is now pretty deep in iOS territory, I'd say the main thing for me has been email. I've used https://www.fastmail.com for a great deal of years now, which is also home to my calendar as well so there's nothing much of value tied to my Google account. YouTube subscriptions would be annoying to lose but... - Source: Hacker News / 6 months ago
  • Ask HN: Tell us about your project that's not done yet but you want feedback on
    You may want to look into https://exist.io/. It's a very indie developer duo out of Australia (IIRC). And also IIRC they were looking for a buyer on Twitter some time ago. - Source: Hacker News / almost 2 years ago
  • Ask HN: Anyone using or working on a life dashboard?
    I have used this previously when tracking health metrics and I couldn't much else that had integrations. https://exist.io/. - Source: Hacker News / almost 2 years ago
  • Tracking Apps
    Hey guys, thinking of tracking wellness metrics such as sleep water intake etc to a dashboard/app. The main tools I have found are Exist.io, Gyrosco.pe, and conjure.so. For those of you who have tried them I would love to know what are the pros and cons with each one? Or if you have any better ones any help is greatly appreciated! Source: almost 2 years ago
  • Best apps to use
    Hey guys, thinking of transporting my quantified self journey to a dashboard/app. The main tools I have found are Exist.io, Gyrosco.pe, and conjure.so. For those of you who have tried them I would love to know what are the pros and cons with each one? Source: almost 2 years ago
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TensorFlow mentions (7)

  • Creating Image Frames from Videos for Deep Learning Models
    Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 2 years ago
  • Need help with a Tensorflow function
    So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 3 years ago
  • Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
    Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: almost 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
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What are some alternatives?

When comparing Exist and TensorFlow, you can also consider the following products

Gyroscope - Gyroscope is a personalized dashboard for tracking your life.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Habitica - Habitica is a free habit building and productivity application.

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

HabitBull - HabitBull

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

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