Launch Tir: GenAI 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.

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 

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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.

Tir: E2E Cloud’s Pricing

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

Free Tier
16 CPU
Our sales representatives are available at +91-11-4084-4965 and
* Price is exclusive of 18% GST Rate
** Monthly Prices shown are calculated using an assumed usage of 730 hr/month; actual monthly costs may vary based on the number of days in a month.

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.

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“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

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