Neuron is a server-less Deep Learning and AI experiment platform for analytics where you can build, deploy and visualise the data models. Practical lab on cloud access from anywhere.

1. Break into the world of Automation,
Analytics & AI
Presenting
Neuron

2. Contents
 What is Neuron?
 Tools
 Why choose Neuron?
 Features
➔ Neuron for Data Scientists
➔ AI Experiments
➔ Deep Learning Models
 Dashboard
 Your team! Your Workspace
 Technology & Solution Providers
 Softwares in use
 Data Science Platform
 Jupyter Notebook
 Zeppelin
 Big Data Platform
 Apache Spark
 FDP Training Program
 Training Program for Professional
 Services
 USP

3. What is Neuron?
● Neuron is a serverless Deep Learning and AI experiment platform for
analytics where you can build, deploy and visualize the data models.
● Practical lab on cloud access from anywhere
Neuron – Bringing AI & Data Together

4. Tools

5. Why choose Neuron?
Technology – Focused on Best Practices and Tools - Engineering Empathy –
Fundamentals - Fundamentals involves intensive task based on cloud Stack Data Labs features emphasis ability to understand
the strong foundation built on Computng, Big Data, Data Science on adopting the best and willingness to internalize
Design thinking, algorithms, & Internet of Things. practices and Tools for developing the feedback are few
analytics & how to solve the innovative & imaging ways practices important to learn
problem to catalyze longness to solve the problems. With professional skills.
and productivity.

6. Features
CNN RNN
GAN Autoencoder
LSTM RCNN
For
Data
Scientists
Technology
Stack
Deep
AI Learning
Experiments Models
Intelligent Bots Auto Scaling
Advanced and
Continuous Optimizing
Monitoring GPU usage
Deploy any ML/DL Workflow with
model in minutes Interactive
Dashboard
Data Data
Explanation Visualization
Machine Deep
Learning Learning
Discussion Analysis

7. Neuron for DataScientists
Data Data
Explanation Visualization
Machine Deep
Learning Learning
Manufacturing
Healthcare
Insurance
Education
Data
Transportation Communication
Consumer Energy
Trade
Analysis
Data
Discussion
Data
Scientist

8. AI Experiments
Intelligent Bots Auto Scaling
Advanced and
Continuous Optimizing
Monitoring GPU usage
Deploy any ML/DL Workflow with
model in minutes Interactive
Dashboard

9. Deep Learning Models
CNN RNN
GAN Autoencoder
LSTM RCNN

10. Dashboard
Neuron dashboard is first
information face to visually
track the status of available
and deployed softwares with
total members.
The interface is a
glance view of key
elements for using
the lab.

11. Your team! Your Workspace!
Xenony
Xenony abc@xenonstack.com

12. Technology & Solution Providers
Open Stack
Docker Kubernetes
Hadoop Apache Spark

13. Softwares in use
Big Data
Apache Spark-
Apache Spark is an
analytics platform
for large-scale
data processing.
Zeppelin-
Apache Zeppelin is a
web-based notebook
that enables data-driven
interactive analytics and
collaborative documents
with Scala, SQL and much
more.
Jupyter Notebook -
Jupyter Notebook is a
development environment
for writing and executing
Python code. The notebook
is often used for analysis
with description and also
for executable documents
to perform data analysis.
Data Science

14. Data Science Platform
Business
Understanding
Modelling Data
Acquisition
Deployment
Feature
Engineering Model
Evaluation
Model
Training
Data
Wrangling
Data Data
Source Cleaning
Data
Exploration
Start
End

15. Jupyter Notebok
What
Jupyter Notebook is a
development environment
for writing and executing
Python code.
Jupyter Console- It is a
terminal with kernels
using Jupyter protocol.
Why
The notebook
is often used for
analysis with description
and also for executable
documents to perform
data analysis.

16. Zeppelin
What
Apache Zeppelin is a
web-based notebook
that enables data-driven
interactive analytics and
collaborative documents
with Scala, SQL and much
more.
2. With Zeppelin there are
possibilities to mix languages
across cells. Zeppelin supports
Scala, Python, SparksSQL,
Hive, Markdown and Shell
and we can make our own
language interpreter.
Why
1. It is data exploration
and visualization intended
for big data and large
scale projects.

17. Big Data Platform

18. Apache Spark
Apache Spark is an analytics Pyspark used in Python is Libraries
platform providing large scale great for performing exploratory PySparkSQL- It is a PySpark
data processing and can be data analysis at scale, building library to apply SQL-like
easily used in applications such machine learning pipelines analysis on huge structured
as Java, Python, Scala, R and and to create ETLs for data and semi-structured data.
SQL platform. Py4J – Popular library which is
integrated within Pyspark and
allows to dynamically
interface JVM objects

19. FDP Training Program
Big Data
Overview
Need of
Big Data
Need of
Apache Spark
Big Data
Landscape
Need of
Hadoop
JVM based
Programming-
Java & Scala

20. Multi-node
deployment
Automation of
Hadoop Clusters
MapReduce
Programming
Hive
Cluster
administration
Pig

21. PlanningData Integration
ETL Deployment
Lambda
Architecture
Designing the
BigData Solutions
Hadoop
Architect
Data
Warehousing Data Pipeline

22. Training Programs For
Professionals
Hadoop
Adminstration
Data
Engineering
BigData
With Java
BigData
Analytics
Big Data Training
Apache Spark
With Python
NoSQL
Essentials

23. OpenStack
Administration
Cloud Computing
Essentials
OpenStack
Professional
AWS
Professional
Azure
Professional
Google Cloud
Professional
Cloud Computing
Training

24. DevOps
Using Puppet
& Chef
DevOps
Essentials
DevOps
Using Ansible
DevOps
Training

25. DataIntegration
Training
Business
Intelligence
Business
Analytics
Business Intelligence
Training

26. Data Scientist
With Python
Data Science
101
R Programming
& Analysis
Text
Analytics
Data Science
Accelerator
Program
IoT Accelerator
Program
Data Science
&
IoT Training

27. UI/UX
Designing
Javascript
Programming
Data Visualization
Overview
Data Visualization
Training

28. Services
● Data Science with Python
● Deep Learning, NLP and Text Analytics
● Big Data Analytics with Scala
● DevOps & Linux- Ansible, Terraform
● Kubernetes & Docker

29. USP
● Build, train and host your models
● Build and host your open source,
innovative and visualize AI projects.
● Tackles complicated projects with
ease.
● Big data platform- manage at one
place
● Minimize strain on production
● Handle many projects in pipeline
● Scale at any deployment option