Bring Machine Learning Inside Your iOS App Development with Core ML

iOS App Development

Remember the movie “Minority Report” where the machines were programmed to predict the murders before they happen, thus reducing murder rate to zero. This is an apt example of machine learning, where based on the past experiences, the machine learns to identify things and adapt to the changes. For example, the emails have become more intelligent and can identify the spam specifically.

This will benefit the businesses that are looking to understand the consumer and offer services/products that cater to their needs specifically.

Apple has been proactively working on incorporating machine learning to their iOS applications. The introduction of Core ML during the Apple’s WWDC proves this. This framework was solely designed to help run the different machine learning models on Apple devices efficiently. With simple integration, this framework helps deliver fast performance of machine learning models.

Let’s take a look at what all you can do with the Core ML framework.

Exploring the Core ML Framework
The Core ML framework allows you to choose from the different pre-trained models or integrate your own machine learning model, depending on your need. There are different machine learning models such as neural networks, tree ensembles, support vector machines etc. You will need to check if the model that you are using can be obtained in the .mlmodelformat. If you are using a model that has been created in a different format, you will need to use the CoreML tools to convert it to an appropriate format before moving on.

The CoreML framework can help you with a lot of features within the applications you are developing. Let’s have a quick look at the possibilities.

1) Facial Recognition: Facebook has been asking questions like “Do you want tag “X” in the photo?” This is an example of facial recognition technology. By combining Vision with CoreML, you can bring machine learning into your apps to facilitate facial recognition, object recognition, barcode detection as well as object tracking. If you can work on the applications to facilitate anticipating user requirements, you can benefit from it majorly
2) NLP: With NLP, recognizing text becomes easy. You can use the different features such as language identification, tokenization, named entity recognition etc. to depict the language. You can integrate this feature into your application with ease with the Core ML framework.

These are just some of the applications of Core ML framework. You will obviously be able to use the framework to integrate better and improved features to your application, thus enhancing the user experience.

Benefits of ML models in iOS Apps
Why should you integrate machine learning models into your iOS apps? If this question has been haunting you, the benefits section will help you.

1) The machine learning model now works within the iOS app and not on a remote server. This reduces the need for data communication
2) The integration helps bridge the gap that existed between the iOS app and machine learning
3) There is more data privacy
4) Even in offline state, your app proves to be useful. It can predict well, and the response time is less
5) The RAM and power consumption is less when this integration occurs

Incorporating ML Models to iOS Apps
Here’s a step by step guide into incorporating the ML models into your iOS apps. For this, you need MAC OS (preferably the latest version), Python, download pip, format converter and Xcode 9. Once you are ready with these things, you can work on integrating the ML models.

1) Start with writing a basic model. You can choose any framework for this. It is a machine learning model, you will need some numeric data. Convert your existing data into numbers. Check out the predictions made. Test some more sample data using this model for predictions
2) Now, convert this ML model to an Xcode accepted format. If you already have a converter, this work is done easily. However, if it is not present, you can download a converter for the same. This is the basic strength of CoreML, which allows you to convert and import models that are built on other frameworks
3) Next, you need to import this to Xcode. This is a simple drag-n-drop process
4) You can now code the model so that it can run the predictions you are expecting from it
5) Compile and run. Test as many times as possible for the outcomes using the iOS simulator.

Now, your ML model has been integrated into your iOS app. You are ready to use the benefits of machine learning in your app to boost your business.

Summing up
Apple has always envisioned bigger and better things to enhance user experience. With the ideal combination of Vision, Core ML, Foundation as well as other ML tools, you are bound to see a transformation in the way mobile apps are developed for iOS. Core ML is all set to offer high-performance, and efficient machine learning apps with easy coding and converting techniques. You have got a gist of how to get your ML model integrated into the iOS app effectively with this tutorial. So, get started and enjoy your futuristic iOS app development.


Things You Should Know About Django Development Before Start a Company

Things You Should Know About Django Development Before Start a Company

It is amazing how Django has grown since inception. Every single time you master a version of Django, you witness the release of the next version.

If you are beginning with Django development services or are planning to start a full-fledged Django development company, here are a few things that you should know to begin with. This will make your life as an entrepreneur easy, and hassle-free.

1 Choose your data storage wisely

MongoDB has received a lot of flak. However, when it comes to fast iteration, there is nothing that can beat this data storage. RDBMS migrations are easier with MongoDB. The datastore offers better control and is a more mature platform today.

Though MongoDB is good, it does not offer the agility Postgre does. For one, Postgre extends support to JSONB without ruining its performance. The Postgre app works effectively for OSX as well.

While both datastores are good, only one will help you complete your project within the stipulated time. It is always a good idea to choose the datastore wisely.

2 Structure with an efficient directory

Most often, you are caught unawares on how to structure your directory. There are different directories that store different apps within, and you need to know them all before you start developing with Django.

1) Apps directory: Stores customized apps

2) Vendor directory: Stores apps that don’t need to be installed

3) Bin directory: Helps automate the tasks

4) Config directory: Stores the database, webserver, supervisor etc.

5) Media directory: Stores images, JavaScript etc.

3 Go Beyond Apache

While we all think Apache when we are looking for webservers, it is time to go beyond Apache. The reason being if you are a beginner Django developer, chances are Apache might seem like Hulk to you. It is complicated and the different configurations take up a lot of time.

On the other hand, Gunicorn seems simple and helps you get the tasks done easily. So next time you are creating a website on your own, you should choose a simpler webserver.

4 Setting it right

It is important to set your settings file right. There are various ways in which you can configure your settings file. One way is to add the local settings to the top directory and then import it to the bottom settings file. There are many other methods of importing the settings file.

You will need to choose wisely.

5 Go with supervisor for process monitoring

Instead of going with a Unix based program to deploy the process monitoring, you should opt for Supervisor. It helps control the processes with ease. It allows you to add separate configuration for the different processes.

6 Use unit testing infrastructure

A test driven development environment seems to be a good idea, even though many developers are set against it. You could instead work on setting up frameworks that allows unit testing environment, thus making project writing and development easy. You can develop small test cases, and use it to test parts of the project.

7 Internal debug toolbar for optimization

The Django-debug-toolbar is an excellent way to debug your program and optimize it for the future. This internal toolbar helps in tracking the performance issues that occur in SQL queries, templates and cache. It is always a good thing to keep optimizing your program right from the start.

8 Choose Redis for Celery

Redis is your best friend for Django development, and this is something you should know from the start. Redis helps queue the Celery jobs and helps store the necessary sessions within Redis. Caching becomes easy with Redis.

9 Jammit is your friend

For those uninitiated to Jammit, it helps with static asset compression, and can be called a Django developer’s best friend. It was initially built to work with Ruby on Rails but is pretty effective on Django as well.

10 Use custom user model

When Django version 1.5 was released, it came with custom user models. This made adding user fields easy and gave a hassle-free alternative to the developer. The inherent field character allocation did not seem enough for the end user which is why the new version came up with the custom user model.

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URLs and Reverse URL

The reverse URL and URL template tag are something every Django developer wishes they knew right at the start. You should name the URLs and refer to them with names in both the template tag and reverse URL files, which is present in the backend. This allows tracking and calling the URLs easy.

Hope these little things about Django development helped you start with your ambitious project. They may seem very primary to begin with but, they help in creating large-scale projects with ease.

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Django vs flask vs pyramid: Which Python Framework Suits your Needs


Almost a decade ago, Java was ruling the roost as it was not only the developer’s preferred platform for development, but also because of its versatility and flexibility. Things have changed in the technology world, with Python walking out of the shadows and progressing ahead of Java as an interpreted, and high-level dynamic programming language that offers flexibility, reusability of code, and high levels compatibility.

Several frameworks have been written in Python, of which Django, Flask and Pyramid are quite popular, and used in developing web applications for enterprises. They are all incredible, and help meet your enterprise goals. The battle is on between the three frameworks, and choosing one among them is proving to be difficult for developers.

Django, Flask and Pyramid are literally fighting for developer’s mindshare tooth and nail.

As a developer, you either have a favorite or, you struggle to choose one among these three. Let’s get an overview of these three frameworks before digging deeper. Flask is a micro web framework, as it does not need tools or libraries, and has no database abstraction layer either. If you want to add features to this web framework, you will need to use extensions. Flask is basically aimed at smaller applications that require simple components.

The Frameworks: General Differences

Django and Pyramid are both open source frameworks developed using Python, and meant for larger applications. These two majorly differ in their techniques, and the way they handle application extensibility and adaptability. In case of Pyramid the developer will need to mix and match components to build the application as in the developer will need to select the URL structure, templating style, database and other related components to build the application. On the other hand, with Django, you will find that everything is in-built, and you will just need to install the framework and start working on the coding and development part. You won’t need to fetch the components or mix-n-match them to your framework. Django consists of the object-relational mapping (ORM) that connects the data models with the relational database to store, save and retrieve the data from the web framework. Flask and Pyramid give the developers the flexibility to choose the method for saving and retrieving data. Preferred ORM for Flask and Pyramid would be DynamoDB or MongoDB as well as regular SQLite.

Now that you have gained an overview into the three frameworks, let’s start comparing the three so as to make choosing the right framework easy for the developers.


When you talk of an open-source framework, you cannot stop from commenting about the community that supports them. Django has the most active community that contains close to 80,000 StackOverflow questions. There are some incredible blogs from the Django developers as well as the users to help develop using this framework.

On the otherhand, both Flask and Pyramid cannot take pride in their community strength, as there are fewer members in them compared to Django. But as far as the mailing lists and IRC activities go, they both have made excellent contribution in here. Of course, the StackOverflow questions for Flask is only 5000, which is lot less than what Django has established. Both star almost equally on Github. You will need a BSD-derived permissive license if you want to use either of these frameworks.

So, when you talk about community and support, you know Django wins hands down.


Bootstrapping is when you can get started with building the application without any external input. When you compare the three frameworks for their bootstrapping capabilities, you will realize the Django and Pyramid both come with in-built bootstrapping tools, while Flask has nothing in-built. You will need to depend on extensions to build the application, as this framework is directed towards small applications alone.

The Flask coding is pretty simple, and easy. So, the learning curve is low, which is also a reason why bootstrapping is not needed for this framework. Flask uses blueprints, in case there is an application that needs more separation among the components.

Pyramid and Django work for bigger projects, which is also the reason why the bootstrapping is required. For Django a project is made of individual applications, and the bootstrapping for Django is created in that manner. Flask and Pyramid treat a project as an entire application. The learning curve for Django is slightly difficult as there are fewer example codes available for this framework.


This will be the final comparison point for all three frameworks. What most developers relate to is an application that can easily and quickly respond to the HTTP requests, while users are interested in using the curl to communicate with the web app.

All three frameworks offer excellent response to HTTP, and offer simple ways to fill in the HTML. With this templating, developers can easily inject information to the web page without using AJAX requires, thus offering exquisite user experience. What happens here is that you just make one round trip to the page and its dynamic data to retrieve results, which is what mobile sites require, as they need load faster for the user to remain put on the application.


Of the three frameworks, Pyramid is the most flexible as it can be used to build both small and large applications. A lot of open source communities trust Pyramid for event-based applications. The only issue with this framework is that it offers many alternatives that can get the developer confused.

Django is pretty popular, and has been used to develop applications such as Pinterest, Instagram etc. For common requirements, Django uses the default practices, and is quite a choice for mid to large segments

If you want to develop a small application and get it launched quickly, then you must use Flask. It can build simple interfaces over existing APIs and create excellent experience.

You will need to choose the framework only after listing your needs, and the timeline. It is always good to have an expert look at your business needs, and understand what you truly want to achieve so that you get quick and incredible solutions. Seashore Partners is a Python development company with an expertise in Django, Pyramid and Flask frameworks. Connect with us over mail for a quick chat on your requirements.

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