Cat or Dog — Image Classification with Convolutional Neural Network

The goal of this post is to show how convnet (CNN — Convolutional Neural Network) works. I will be using classical cat/dog classification example described in François Chollet book — Deep Learning with Python. Source code for this example is available on François Chollet GitHub. I’m using this source code to run my experiment.

Convnet works by abstracting image features from the detail to higher level elements. An analogy can be described with the way how humans think. (more...)

Metrics Driven Blue-green Deployments using Spinnaker’s Cloud Foundry Integration

I recently attended CF Summit in Philadelphia in March 2019 and here is the talk track to that.

Metrics Driven Blue-green Deployments using Spinnaker’s Cloud Foundry Integration - Amith Nambiar & Pas Apicella, Pivotal

https://www.youtube.com/watch?v=9C8m7n_sG38 

Any App, Every Cloud, One Platform: Delivering on Pivotal’s Vision

Pivotal Cloud Foundry (PCF) recently turned five-years-old. In celebration, Onsi Fakhouri reflects on how far the platform has come, and provides a look at our plans for the months and years ahead.

The Pivotal Blog post exists here:

https://content.pivotal.io/blog/any-app-every-cloud-one-platform-delivering-on-pivotal-s-vision

Run Oracle VBCS Application on Your Own Server

Latest VBCS release brings an option to export VBCS application and run on your own server (or different cloud provider). This is a truly strong step forward for VCBS. Read more about it in Shay Shmeltzer blog post. If you decide to keep running VBCS app within VBCS itself, then you get additional functionality of VBCS Business Services, Oracle Cloud security, etc. out of the box. If you export VBCS application and run on your (more...)

Build it Yourself — Chatbot API with Keras/TensorFlow Model

Is not that complex to build your own chatbot (or assistant, this word is a new trendy term for chatbot) as you may think. Various chatbot platforms are using classification models to recognize user intent. While obviously, you get a strong heads-up when building a chatbot on top of the existing platform, it never hurts to study the background concepts and try to build it yourself. Why not use a similar model yourself. Chatbot implementation (more...)

Publishing Machine Learning API with Python Flask

Flask is fun and easy to setup, as it says on Flask website. And that's true. This microframework for Python offers a powerful way of annotating Python function with REST endpoint. I’m using Flask to publish ML model API to be accessible by the 3rd party business applications.

This example is based on XGBoost.

For better code maintenance, I would recommend using a separate Jupyter notebook where ML model API will be published. Import Flask (more...)

Deploying an Application to Pivotal Cloud Foundry through Spinnaker and then invoking a resize operation

In this post we show a basic deployment to Cloud foundry in fact Pivotal Cloud foundry 2.4 using spinnaker 1.13.0.

Assumptions:

1. Configured a Cloud Foundry provider as shown below

spinnaker@myspinnaker-spinnaker-halyard-0:/workdir$ hal config provider cloudfoundry account add pez208 --user admin --password mypassword --api api.system.run.myenv.io --environment dev --appsManagerURI https://apps.system.run.myenv.io
+ Get current deployment
  Success
+ Add the pez208 account
  Success
Problems in default. (more...)

Two nice Pivotal Container Service (PKS) CLI commands I use very often

Having always created multiple PKS clusters at times I forget the configuration of my K8S clusters and this command comes in very handy

First lets list those clusters we have created with PKS

papicella@papicella:~$ pks clusters

Name    Plan Name  UUID                                  Status     Action
lemons  small      5c19c39e-88ae-4e06-a1cf-050b517f1b9c  succeeded  CREATE
banana  small      7c3ab1b3-a25c-498e-8179-9a14336004ff  succeeded  CREATE

Now (more...)

Selecting Optimal Parameters for XGBoost Model Training

There is always a bit of luck involved when selecting parameters for Machine Learning model training. Lately, I work with gradient boosted trees and XGBoost in particular. We are using XGBoost in the enterprise to automate repetitive human tasks. While training ML models with XGBoost, I created a pattern to choose parameters, which helps me to build new models quicker. I will share it in this post, hopefully you will find it useful too.

I’m (more...)

Prepare Your Data for Machine Learning Training

The process to prepare data for Machine Learning model training to me looks somewhat similar to the process of preparing food ingredients to cook dinner. You know in both cases it takes time, but then you are rewarded with tasty dinner or a great ML model.

I will not be diving here into data science subject and discussing how to structure and transform data. It all depends on the use case and there are so (more...)

Spring Initializr new look and feel

Head to http://start.spring.io and the new look and feel UI is now available


Oracle JET Table with Template Slots for Custom Cells

Oracle JET table comes with template slot option. This is helpful to build generic functionality to render custom cell within the table.

In this example, custom cells are used to render dates, amount and risk gauge:


While implementing Oracle JET table it is a best practice to read table column structure from a variable, not to define the entire structure in HTML itself. Property columns refer to the variable. Template called cellTemplate is a default (more...)

Intercepting ADF Table Column Show/Hide Event with Custom Change Manager Class

Ever wondered how to intercept ADF table column show/hide event from ADF Panel Collection component? Yes, you could use ADF MDS functionality to store user preference for table visible columns. But what if you would want to implement it yourself without using MDS? Actually, this is possible through custom persistence manager class. I will show you how.

If you don't know what I'm talking about. Check below screenshot, this popup comes out of the box (more...)

ADF Performance Improvement with Nginx Compression

We are using Nginx web server for Oracle ADF WorkBetter hosted demo hosted on DigitalOcean cloud server. Nginx helps to serve web application content fast and offer improved performance. One of the important tuning options - content compression, Nginx does this job well and is simple to setup.

Content compression doesn't provide direct runtime performance, a browser would run the same code, doesn't matter it was compressed or not. But it brings improved perceived performance (which (more...)

Integrating Cloud Foundry with Spinnaker

I previously blogged about "Installing Spinnaker on Pivotal Container Service (PKS) with NSX-T running on vSphere" and then how to invoke UI using a "kubectl port-forward".

http://theblasfrompas.blogspot.com/2019/02/installing-spinnaker-on-pivotal.html
http://theblasfrompas.blogspot.com/2019/02/exposing-spinnaker-ui-endpoint-from.html

Steps

1. Exec into hal pod using a command as follows:

$ kubectl exec --namespace default -it myspinnaker-spinnaker-halyard-0 bash

Note: You can get the POD name as follows

papicella@papicella:~$ kubectl get pods | grep halyard
myspinnaker-spinnaker-halyard-0       1/1      (more...)

Jupyter Notebook — Forget CSV, fetch data from DB with Python

If you read a book, article or blog about Machine Learning — high chances it will use training data from CSV file. Nothing wrong with CSV, but let’s think if it is really practical. Wouldn’t be better to read data directly from the DB? Often you can’t feed business data directly into ML training, it needs pre-processing — changing categorial data, calculating new data features, etc. Data preparation/transformation step can be done quite easily with (more...)

Exposing Spinnaker UI endpoint from a helm based spinnaker install on PKS with NSX-T

I previously blogged about "Installing Spinnaker on Pivotal Container Service (PKS) with NSX-T running on vSphere" and then quickly invoking the UI using a "kubectl port-forward" as per this post.

http://theblasfrompas.blogspot.com/2019/02/installing-spinnaker-on-pivotal.html

That will work BUT but it won't get you too far so his what you would need to do so the UI works completely using the spin-gate API endpoint.

Steps (Once Spinnaker is Running)

1. Expose spin-deck (more...)

Spring Cloud GCP and authentication from your Spring Boot Application

When using Spring Cloud GCP you will need to authenticate at some point in order to use the GCP services. In this example below using a GCP Cloud SQL instance you really only need to do 3 things to access it externally from your Spring Boot application as follows.

1. Enable the Google Cloud SQL API which is detailed here

  https://cloud.google.com/sql/docs/mysql/admin-api/

2. Ensure that your GCP SDK can login to your Google (more...)

JDeveloper 12c IDE Performance Boost

There is a way to optimize JDeveloper 12c IDE performance by disabling some of the features you are not using.

I was positively surprised with improved JDeveloper responsiveness after turning off some of the features. ADF BC, Task Flow, and ADF Faces wizards started to respond in a noticeably faster way. Simple change and big performance gain, awesome.

One of the strongest JDeveloper performance improvements come from disabling TopLink feature. Ironically - TopLink is an (more...)

Cross Field Form Validation in Oracle JET

JET keeps evolving and in the latest versions  - toolkit provides improved support for form cross-field validation. It is much easier to implement validation than it was before. I will show it in this example.

Example of the data entry form. Validation logic:

- Invoice Date before Payment Due Date and Payment Date
- Payment Due Date before Payment Date


Example when two fields fail validation:


JET provides component called validation group. Form can be (more...)