 
                 
                        ( without GPU )
Supports all popular Deep Learning Packages
Tensor Flow,  Keras, PyTorch, Scikit-Learn, Pandas, NumPy, NLTK
Supports all popular Deep Learning Architecture/Deep Convolutional Networks
SNN, RNN, Perceptron, YOLO , Back Propagation, Auto Encoders
Indicative configurations for existing Desktops/Workstations
WOCLO framework
I-5 or I-7, 8 to 16 GB, 1TB of SSD ( 3 K ), Switch ( min of  1-Gigabit ) 
 
                        ( with GPU )
All popular Deep Learning Packages
Tensor Flow, Keras, Caffe, PyTorch, Scikit-Learn, Theano, MXNet, Pandas, NumPy, NLTK
All popular Deep Learning Architecture/Deep Convolutional Networks
AlexNet, Google Inception Models, VGG Net, ResNet, RCNN/Faster RCNN, YOLO Version Etc
Indicative Configurations - Desktops/Workstations
AI Server with Dual Processor and 2 Nvidia A100 GPU, 256 GB RAM, 8-TB SSD 
 
                        Data Science lab by repurposing existing hardwares
Hadoop (HDFS, MR,Yarn), Hive, Pig, Spark, MR-2, HDFS based DBs, Hbase, etc.
NoSQL ( MongoDB and Cassandra )
Analytics Modules ( All the related python modules )
Analytic Engines - Kibana, Grafana and Tableau
Multi User Accessibility
Indicative configurations for existing Desktops/Workstations
I-5 or I-7, 8 to 16 GB, 1TB of SSD ( 3 K ), Switch ( min of 1 Gigabit ) 
Designing labs/sessions capabilities
           Inbuilt Question Bank
           Predefined Sessions
Students/HODs/Parents and Faculties logins
          Lab-records, study material provided by faculties
          Marks managements etc.
State of the art tracking capabilities at all levels/roles
Support for QCM (Quality Check Management)  
                                                     Dashboard
                                                     Platform
                                                     Sessions
                                                     Live Labs 
                                                     Stats
                                                     Misc 
                            
                       Student, faculty, HOD, Management, Parents
                       Integrated for Data Science
                       Deep learning, Big Data, Data Analytics
                       Access to Management, HOD, Faculty
                       Available to Management, HOD, Faculty
                       Attendance, Lab Reports, Technical Examples 
                                                       Model
                                                       Environment
                                                       Prime Modules
                                                       Misc
                            
                         Includes 12 system configurations OR GPU      setup
                         Jupyter Hub with Plugins
                         Keras, Tensor flow, Sci-kit, Open CV, etc.
                         Multi User Accessibility  
                                                      Core Components
                                                      Eco System
                                                      Engines
                                                      HDFS based DBs
                                                      Misc 
                            
                        Hadoop ( HDFS, MR, Yarn ) - 3 clusters
                        Hive, Pig
                        Spark, MR-2
                        Hbase
                        Multi User Accessibility, Handbook 
 
                        If you are a school running for specially skilled students or Orphans.
 
                        If you are a school of less than 100 - then our charges are as much less as 1000/-
 
                        If you are running non-Profitable/ Charitable schools and cannot afford our services.