Launch Tir: E2E Cloud’s Flagship Machine Learning Platform.

Tir is built on top of Jupyter Notebook, an advanced web-based interactive development environment offered by E2E Cloud. It provides users with the latest features and functionalities, including JupyterLab, a cutting-edge interface for working with notebooks, code, and data. JupyterLab empowers users to effortlessly customize and streamline their workflows across diverse domains like data science, scientific computing, computational journalism, and machine learning.

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Users have the flexibility to configure and organize their workflows according to their specific needs and preferences. The modular design of JupyterLab also enables the integration of extensions, allowing users to expand and enhance its functionality to suit their specific needs. Most importantly, Tir allows you to take control of your data science stack, without having to rely on additional help.

Learn more about Jupyter Notebook

GPU Jupyter Notebook

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“Collaborate with your team in real-time, enabling multiple users to work on the same notebook simultaneously”

When using Jupyter Notebook through E2E Cloud, you can expect the following technical specifications:

Flexible and Scalable Infrastructure

E2E Cloud provides a robust infrastructure to support Jupyter Notebook, ensuring high performance and scalability for your computational needs. You can easily scale up or down your resources based on your requirements.

Latest Jupyter Notebook Version

E2E Cloud keeps up with the latest versions of Jupyter Notebook, ensuring that you have access to the most recent features, improvements, and bug fixes.

Multi-Language Support

Jupyter Notebook offers comprehensive support for multiple programming languages, including Python, R, Julia, and numerous others. This extensive language support allows users to work with their preferred programming languages and take advantage of the vast ecosystem of libraries and tools available in each language.

Notebook Sharing and Collaboration

E2E Cloud's Jupyter Notebook environment enables seamless sharing and collaboration. You can share your notebooks with team members or the wider community, facilitating collaborative research, code reviews, and knowledge exchange.

Why launch a Jupyter Notebook on E2E Cloud?

Launching GPU Jupyter Notebooks on E2E Cloud offers numerous advantages, making it an ideal choice for users. Here are USPs of why people should choose E2E Cloud for launching GPU Jupyter Notebooks:

1. Cost-effectiveness:

E2E Cloud provides highly competitive pricing in the Indian and global markets, offering cost-effective solutions for running GPU Jupyter Notebooks. This allows users to optimize their expenses while benefiting from powerful GPU capabilities.

2. Industry-leading infrastructure:

E2E Cloud is a NSE-Listed AI-First Hyperscaler known for its robust and reliable infrastructure. By choosing E2E Cloud, users can leverage a stable and secure environment for running GPU Jupyter Notebooks.

3. Flexible per-hour pricing:

E2E Cloud offers flexible per-hour pricing options, allowing users to pay only for the resources they consume. This pricing model enables cost optimization and scalability, as users can scale their GPU Jupyter Notebooks as per their requirements.

4. High-performance GPUs:

E2E Cloud supports running NVIDIA GPUs, which are renowned for their exceptional performance in various compute-intensive tasks, including machine learning and data analysis. Users can benefit from industry-vetted GPU performance for their Jupyter Notebook workloads.

5. Global accessibility:

E2E Cloud caters to customers not only in India but also in the global market. Users from different geographic locations can launch GPU Jupyter Notebooks on E2E Cloud, enjoying its competitive pricing, powerful infrastructure, and extensive capabilities regardless of their location.

Related Blogs & Resources

Launch of Tir: Jupyter Notebook on E2E Cloud

E2E Cloud has recently launched Jupyter Notebook As a Service. In this blog, learn how you, as a data scientist, can leverage it.

How Can Data Scientists Leverage The Power of GPU Jupyter Notebooks To Accelerate Deep Learning Tasks?

Jupyter Notebooks play a crucial role in data science because they significantly contribute to the entire data analysis and modeling process.

How can E2E Cloud's competitive pricing and performance enhance your GPU Jupyter Notebook experience?‍

In the realm of data science and technical research, Jupyter Notebook has emerged as an indispensable tool, revolutionizing the way professionals work with data, experiment with code, and collaborate on projects.

“Develop and train machine learning models using popular frameworks like TensorFlow, PyTorch, or Scikit-learn within Jupyter Notebook”

Real-world use cases that showcase why E2E Cloud should be the preferred choice for launching GPU Jupyter Notebooks:

Deep Learning and Neural Networks:

E2E Cloud's GPU Jupyter Notebook environment enables researchers and data scientists to train complex deep learning models efficiently. By leveraging the power of GPUs, they can accelerate the training process, enabling faster iterations and better model performance.

Data Analytics and Visualization:

With the ability to handle large datasets and perform complex data transformations, GPU Jupyter Notebooks on E2E Cloud are ideal for data analytics and visualization. Users can leverage GPUs to accelerate computations, enabling faster data exploration, analysis, and visualization.

Training and Launching LLMs:

Training and launching Large Language Models (LLMs) involves collecting a diverse dataset, preprocessing the data, selecting an appropriate model architecture such as transformer-based models, training the model using powerful hardware and computational resources, tuning hyperparameters, evaluating model performance, and deploying the model for use. Ethical considerations, including bias detection and mitigation, privacy, and transparency, should be addressed throughout the process. Continuous monitoring and iteration are crucial for improving the model's performance and addressing any limitations or biases that may arise during real-world usage.

Financial Modeling and Quantitative Analysis:

Financial modeling and quantitative analysis demand high-performance computing capabilities. By utilizing GPU Jupyter Notebooks on E2E Cloud, finance professionals can leverage GPUs for rapid financial modeling, risk analysis, and algorithmic trading strategies.

Data Science and Machine Learning:

Data Science is an interdisciplinary field that combines statistics, mathematics, computer science, and domain expertise to extract insights and knowledge from structured and unstructured data. Machine learning is a subset of artificial intelligence that focusses on developing algorithms and models that enable computers to learn from data and make predictions.

Accelerate Machine Learning and Deep Learning Workloads with up to 70% cost-savings.

Benefits of E2E GPU Cloud

No Hidden Fees

No hidden or additional charges. What you see on pricing charts is what you pay.

NVIDIA Certified Elite CSP Partner

We are NVIDIA Certified Elite Cloud Service provider partner. Build or launch pre-installed software Cloud GPUs to ease your work

NVIDIA Certified Hardware

We are using NVIDIA certified hardware for GPU accelerated workloads.

Flexible Pricing

We are offering pay as you go model to long tenure plans. Easy upgrade allowed. Option to increase storage allowed.

GPU-accelerated 1-click NGC Containers

E2E Cloud GPUs have super simple one click support for NGC containers for deploying NVIDIA certified solutions for AI/ML/NLP/Computer Vision and Data Science workloads.

How E2E GPU Cloud is helping Cloud Quest in their gaming journey

Latency is a critical part of Cloud Gaming. E2E GPU Cloud provided ultra-low network latency to Cloud Quest users and enhanced their gaming experience.

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We at CamCom are using E2E GPU servers for a while now and the price-performance is the best in the Indian market. We also have enjoyed a fast turnaround from the support and sales team always. I highly recommend the E2E GPU servers for machine learning, deep learning and Image processing purpose.

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The customer support that E2E has provided us is beyond exceptional. Their quick response is what makes them stand apart from others and is second to none in the cloud space. We've been using their GPU instances for our Deep Learning workloads for quite a long time. The quality of service is amazing at a competitive price and we strongly recommend E2E.

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About Us

E2E Networks Ltd is an India-focused Cloud Computing Company, pioneering the introduction of contract-less cloud computing for Indian startups and SMEs. The E2E Networks Cloud has been employed by numerous successfully scaled-up startups such as Zomato, Cardekho, Healthkart, Junglee Games, 1mg, and many others. It played a crucial role in facilitating their growth from the startup stage to achieving multi-million Daily Active Users (DAUs).

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Frequently Asked Questions (FAQs)

Why choose E2E Cloud for launching your GPU Jupyter Notebook?
Here are 10 frequently asked questions to help you make an informed decision:

What is a GPU-backed Jupyter Notebook, and how does it benefit data scientists and machine learning practitioners?

A GPU backed Jupyter Notebook combines the power of JupyterLab, a versatile web-based development environment, with GPU capabilities for accelerated computing. It enables data scientists and ML practitioners to leverage GPUs for faster computation, making complex tasks more efficient and scalable.

Why should I choose E2E Cloud for my GPU backed Jupyter Notebook deployment?

E2E Cloud is a highly reputed cloud infrastructure company with a strong presence in the GPU cloud provider market. Our competitive pricing, both in India and globally, ensures cost-effectiveness without compromising performance. With E2E Cloud, you get industry-vetted GPU performance coupled with flexible per-hour pricing.

Can I run NVIDIA GPUs on E2E Cloud for my GPU backed Jupyter Notebook?

Absolutely! E2E Cloud supports NVIDIA GPUs, allowing you to harness their power for your data science and machine learning workloads. Benefit from the cutting-edge capabilities of NVIDIA GPUs while enjoying the convenience and flexibility of E2E Cloud's infrastructure.

Are there any limitations on the GPU resources I can access on E2E Cloud?

E2E Cloud provides access to a wide range of GPU resources to cater to different requirements. Whether you need entry-level GPUs or high-end models, E2E Cloud offers flexibility in choosing the right GPU resources to match your workload demands.

Is there any flexibility in pricing for GPU backed Jupyter Notebook?

Yes, E2E Cloud offers flexible per-hour pricing for your GPU backed Jupyter Notebook instances. This means you only pay for the computing resources you use, providing cost-efficiency and scalability for your projects.

How does E2E Cloud's pricing compare to other cloud providers in the market?

E2E Cloud is known for its highly competitive pricing in the Indian and global markets. Our rates are lower compared to many other cloud providers, making us an ideal choice for cost-conscious customers seeking top-notch GPU infrastructure.

Can I customize and configure my GPU-backed Jupyter Notebook environment on E2E Cloud?

Absolutely! With E2E Cloud, you have complete control over your GPU Jupyter Notebook environment. You can easily configure and arrange workflows in JupyterLab, install custom packages, and leverage the modular design to extend functionality based on your specific needs.

Is E2E Cloud suitable for both small-scale projects and large-scale deployments?

Yes! E2E Cloud caters to projects of all sizes, ranging from small-scale experiments to large-scale deployments. Our infrastructure is designed to scale seamlessly, ensuring that you can meet the demands of your projects, regardless of their size.

Can I collaborate and share my GPU-backed Jupyter Notebook projects with others on E2E Cloud?

Yes, E2E Cloud supports collaboration and sharing features for your GPU Jupyter Notebook projects. You can easily share notebooks, collaborate with team members, and foster a productive environment for data science and machine learning initiatives.

How reliable and secure is E2E Cloud for hosting my GPU-backed Jupyter Notebook?

E2E Cloud prioritizes reliability and security. With robust infrastructure, industry-standard security measures, and regular backups, we ensure the safety and integrity of your GPU Jupyter Notebook instances. Focus on your work with peace of mind, knowing that your data is in capable hands.

How is the monthly pricing calculated?

Monthly prices shown are calculated using an assumed usage of 730 hours per month; actual monthly costs may vary based on the number of days in a month.

Do you include Tax in the prices listed on the website?

No price is exclusive of any taxes, all plan pricing is subject to 18% GST rate.

Learn more about E2E Networks

E2E Networks Ltd is an India focused Cloud Computing Company and the first to bring contract-less cloud computing to the Indian startups and SMEs.

Co-founded by veterans Tarun Dua and Mohammed Imran, E2E Networks Cloud was used by many of the successfully scaled-up startups like Zomato/Cardekho/Healthkart/Junglee Games/1mg and many more to scale during a significant part of their journey from startup stage to multi-million DAUs (Daily Active Users).In 2018, E2E Networks Ltd issued its IPO through NSE Emerge and was oversubscribed 70 times!

Today, E2E Networks is the largest NSE listed Cloud Provider having served more than 10,000 customers and having thousands of active customers.E2E Networks is the platform of choice for Cloud Infrastructure used by Indian entrepreneurs since 2009.

Will my billing stop if I switch off the server?

No. The billing will continue even if you switch off the server as we cannot provide the same server to any other customer. Only when the server is terminated/ deleted, the billing stops. Customers can attach the Block storage with E2E Cloud GPUs, save all the data in the Block storage, take the image and then terminate the Cloud GPUs. Next time whenever they need, a Cloud GPU server can be launched from the saved image and attached with the block storage.

“Start your GPU-backed Jupyter Notebook journey on E2E Cloud today and experience the power and flexibility of accelerated computing combined with a reliable and cost-effective cloud infrastructure.”

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