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Neural Networks and Deep Learning VS Looker

Compare Neural Networks and Deep Learning VS Looker and see what are their differences

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Neural Networks and Deep Learning logo Neural Networks and Deep Learning

Core concepts behind neural networks and deep learning

Looker logo Looker

Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
  • Neural Networks and Deep Learning Landing page
    Landing page //
    2021-07-27
  • Looker Landing page
    Landing page //
    2023-10-11

Looker is a business intelligence platform with an analytics-oriented application server that sits on top of relational data stores. The Looker platform includes an end-user interface for exploring data, a reusable development paradigm for creating data discovery experiences, and an extensible API set so the data can exist in other systems. Looker enables anyone to search and explore data, build dashboards and reports, and share everything easily and quickly.

Neural Networks and Deep Learning features and specs

  • Accuracy
    Neural networks, especially deep learning models, have achieved state-of-the-art performance on many complex tasks, such as image and speech recognition, due to their high capacity for learning intricate patterns in data.
  • Flexibility
    Deep learning models can be applied to a wide range of problems—from image and video processing to natural language processing—due to their versatile architecture.
  • Feature Learning
    Neural networks can automatically learn and extract features from raw data, reducing the need for manual feature engineering.

Possible disadvantages of Neural Networks and Deep Learning

  • Compute Resources
    Training deep learning models often requires significant computational power, such as GPUs, and can be time-consuming and expensive.
  • Data Requirements
    Deep learning models generally require large amounts of labeled data to train effectively, which can be a limitation in domains where data is scarce.
  • Interpretability
    Neural networks are often considered to be 'black boxes' due to their complex architectures, making it difficult to interpret and understand how they make decisions.

Looker features and specs

  • Powerful Data Modeling
    Looker uses LookML, a proprietary modeling language, making it possible to transform raw data into meaningful metrics and dimensions, providing deep insights without needing SQL expertise.
  • Ease of Use
    Its intuitive user interface enables non-technical users to create visualizations and reports with relative ease, reducing the workload on data teams.
  • Customization
    Looker offers extensive customization options for data exploration and visualization, allowing dashboards and reports to be tailored to specific user needs.
  • Embedded Analytics
    Provides robust capabilities for embedding analytics into applications or portals, broadening the scope of data-driven decision-making throughout the organization.
  • Real-time Data
    Supports real-time data analytics by querying live data, which ensures up-to-date insights and helps in making timely decisions.
  • Integrations
    Looker integrates seamlessly with a wide range of databases and cloud data warehouses, including Google BigQuery, Amazon Redshift, and Snowflake.

Possible disadvantages of Looker

  • Learning Curve
    LookML, while powerful, can be complex for beginners who are not already familiar with data modeling or SQL, resulting in a steep learning curve.
  • Cost
    Looker can be expensive, especially for small businesses, as pricing is typically based on the number of users and the data volume processed.
  • Performance
    Query performance can sometimes be slow, especially with complex data models and large data sets, which may impact the user experience.
  • Customization Constraints
    While Looker offers great customization, certain advanced customizations may require significant expertise and time, posing a potential barrier.
  • Limited Offline Capabilities
    Looker is primarily designed for online use, so it lacks robust offline capabilities, which can be a limitation for users who need access to data in situations without internet connectivity.

Neural Networks and Deep Learning videos

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Looker videos

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Looker Review

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  • Tutorial - How To Use Looker as a Business User
  • Review - Looker Review - Off The Shelf Reviews

Category Popularity

0-100% (relative to Neural Networks and Deep Learning and Looker)

Neural Networks and Deep Learning

Looker

AI
100 100%
AI
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Business Intelligence
0 0%
Business Intelligence
100% 100

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Neural Networks and Deep Learning and Looker

Neural Networks and Deep Learning Reviews

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Looker Reviews

Explore 7 Tableau Alternatives for Data Visualization and Analysis
Looker Studio, formerly Google Data Studio, is a user-friendly business intelligence tool that transforms raw data into interactive, customizable dashboards and reports. It integrates seamlessly with Google's ecosystem and supports various data sources, including Google Analytics and BigQuery. Looker Studio offers robust visualization capabilities and real-time collaborative...
Source: www.draxlr.com
Explore 6 Metabase Alternatives for Data Visualization and Analysis
To find the best Metabase alternative for your business, start by listing your specific requirements, such as customer support, data integrations, visualization options, user access controls, and budget. Compare these needs with the features of other BI tools like Draxlr, Tableau, Power BI, Looker, or Holistics. Once you've identified a few suitable options, take advantage...
Source: www.draxlr.com
5 best Looker alternatives
In this blog, we’ll dive into the best 5 Looker alternatives currently dominating the market. Whether you're seeking a Looker alternative with enhanced features, better pricing, or a more tailored fit for your analytics needs, this guide will help you discover BI tool that could be a perfect match for your business.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Exploring alternatives to Looker isn't just about finding a different tool; it's about uncovering solutions that better address your specific business challenges and operational workflows. Here, we highlight five areas where Looker's limitations might lead you to consider other options.
Source: www.sigmacomputing.com
6 Best Looker alternatives
So who are Looker’s competitors? Our top 5 Looker alternatives provide data visualisation and exploration for business intelligence but also offer lower price points, less of a learning curve, and more accessibility for your non-tech team.
Source: trevor.io

Social recommendations and mentions

Based on our record, Neural Networks and Deep Learning should be more popular than Looker. It has been mentiond 49 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.

Neural Networks and Deep Learning mentions (49)

  • Ask HN: How to learn AI from first principles?
    3 ~[Dive into Deep Learning](https://d2l.ai/)~ - Going deep into DL, including contemporary ideas like Transformers and Diffusion models. ⠀~[Neural networks and Deep Learning](http://neuralnetworksanddeeplearning.com/)~ could also be a great resource but the content probably overlaps significantly with 3. Would anybody add/update/remove anything? (Don't have to limit recommendations to textbooks. Also open to... - Source: Hacker News / 4 months ago
  • Phi4 Available on Ollama
    How come models can be so small now? I don't know a lot about AI, but is there an ELI5 for a software engineer that knows a bit about AI? For context: I've made some simple neural nets with backprop. I read [1]. [1] http://neuralnetworksanddeeplearning.com/. - Source: Hacker News / 4 months ago
  • 5 Free Tools to Simplify Learning Neural Networks
    A free book with visuals and examples to simplify neural networks and advanced concepts like CNNs. Course Link. - Source: dev.to / 6 months ago
  • Ask HN: What are some "toy" projects you used to learn NN hands-on?
    Http://neuralnetworksanddeeplearning.com/ Coded everything from scratch, first in elixir, then rewritten some parts in C. - Source: Hacker News / 9 months ago
  • One Bit Explainer: Neural Networks
    That is why I decided to create this entry. Also, while researching, I found the Neural Networks and Deep Learning book by Michael Nielsen, which has great explanations and helped me grasp some basic concepts. - Source: dev.to / 11 months ago
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Looker mentions (14)

  • edit home page to add folder section
    Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the folders if you have set the permissions correctly for each folder). Source: about 2 years ago
  • Stars, tables, and activities: How do we model the real world?
    Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins that can make Kimball warehouses hard to navigate for business users. - Source: dev.to / over 2 years ago
  • dbt for Data Quality Testing & Alerting at FINN
    We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / about 3 years ago
  • I'm a dev ID 10 T please help me
    Dashboard: I like to use Datastudio because it's easy (just like using google sheets), but you can also try out Looker. Source: over 3 years ago
  • The Data Stack Journey: Lessons from Architecting Stacks at Heroku and Mattermost
    For Growth and larger, I would recommend Looker. The only reason I wouldn't recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase. With Looker, you define your data model in LookML, which Looker then uses to provide a drag-and-drop interface for end-users that enables them to build their own visualizations without needing to write SQL. This lets your... - Source: dev.to / over 3 years ago
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What are some alternatives?

When comparing Neural Networks and Deep Learning and Looker, you can also consider the following products

DeepMind - We're committed to solving intelligence, to advance science and humanity.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Deep Learning Gallery - A curated list of awesome deep learning projects

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

OpenAI - GPT-3 access without the wait

Sisense - The BI & Dashboard Software to handle multiple, large data sets.

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