Pinned Repositories
MEA-Regional-Event-Data-AI
These are all the resources for the MEA Regional Event - Data Science & AI for Everyone (https://www.crowdcast.io/e/ddc-mea2021/1) that was a part of the Digital Developer Conference: Data & AI (https://ibm.biz/devcon-ai)
YPDL-SentimentAnalysis-LR
While Deep Learning is a subset of Machine Learning, the prediction methodology in deep learning is different and works similar to how a human brain uses neural pathways to process information & learn from it. In this workshop we will learn about the building blocks of deep learning, neural networks, and how they work. We'll start with Logistic Regression - a simple and basic neural network classification algorithm, having just a one-layer neural network. These are the resources for the first session of Your Path to Deep Learning.
assembly-watson-discovery
Code & data sets for Watson Discovery Workshop - Slides: https://ibm.box.com/v/assembly-watson-discovery
assembly-watsonvr
Code & training sets for Watson Visual Recognition Workshop
CI-For-Node
IRC-Client
IRIS Chat - a Node.js IRC client
naisofly
OfflineSync
Static-Malware-Analysis
Static Feature Extraction & Selection (used in conjunction with the MASTIFF framework)
stepiot
naisofly's Repositories
naisofly/naisofly
naisofly/OfflineSync
naisofly/assembly-watsonvr
Code & training sets for Watson Visual Recognition Workshop
naisofly/assembly-watson-discovery
Code & data sets for Watson Discovery Workshop - Slides: https://ibm.box.com/v/assembly-watson-discovery
naisofly/CI-For-Node
naisofly/CodersHQ
Social platform for developers to network, create and challenge themselves
naisofly/devrel-content
Project to track content creation requests and progress for the Postman Developer Relations team.
naisofly/directory
Directory for Ambassadors of the National Program For Coders
naisofly/dmls-book
Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)
naisofly/engineering-class
Lightning Bits: Engineering for Researchers repo
naisofly/first-bit
Contribute your first bit to Open Source.
naisofly/gitexMarbles
naisofly/lightning
The most intuitive, flexible, way for researchers, ML engineers and data scientists to build models (with PyTorch) and ML systems for the ML lifecycle with an obsessive focus on flexibility and performance.
naisofly/marbles-20181009115320469
Created for toolchain: https://console.ng.bluemix.net/devops/toolchains/9d7113b3-db01-43d8-af38-0e255f56610b?env_id=ibm%3Ayp%3Aus-south
naisofly/marbles-20181017065354526
Created for toolchain: https://console.bluemix.net/devops/toolchains/b79bda2f-ca11-422d-844a-912f6ad17339?env_id=ibm%3Ayp%3Aeu-gb
naisofly/marbles-20181017134928506
Created for toolchain: https://console.bluemix.net/devops/toolchains/63a3eb96-253d-437b-967e-89c70f7323bf?env_id=ibm%3Ayp%3Aeu-gb
naisofly/markdown-portfolio
naisofly/node-s2i-openshift
Example Health is a pretend/conceptual healthcare/insurance type company. It has been around a long time, and has 100s of thousands of patient records in an SQL database connected to a mainframe. This repo houses the UI/Service a client/patient would interact with.
naisofly/openwhisk-darkvisionapp
Created for toolchain: https://console.bluemix.net/devops/toolchains/290654d7-1858-45e5-8fa1-cd733f2f51de?env_id=ibm%3Ayp%3Aus-south
naisofly/sample-nai-devadv-toolchain
Created for toolchain: https://console.bluemix.net/devops/toolchains/5b7e9eb5-08a8-4499-841f-fff4adf94e3d?env_id=ibm%3Ayp%3Aus-south
naisofly/slides_to_pages
naisofly/StartHub
Bootstrap your search for career!
naisofly/surrealdb
A scalable, distributed, collaborative, document-graph database, for the realtime web
naisofly/surrealml
naisofly/talks
Copy of talks and workshops
naisofly/testContainerToolchain
Created for toolchain: https://console-regional.ng.bluemix.net/devops/toolchains/30480acf-e2a2-4ff0-b2cd-da8107ddc89e
naisofly/vehicle-manufacture-20180428160717367
Created for toolchain: https://console.ng.bluemix.net/devops/toolchains/c1a4f2d2-15d0-49b0-a7ad-d6b88dcad671?env_id=ibm%3Ayp%3Aus-south
naisofly/VueAndIBMsCloud
naisofly/website
Source for https://fullstackdeeplearning.com
naisofly/YPDL-Build-a-movie-recommendation-engine-with-TensorFlow
In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.