Machine Learning And Artificial Intelligence Using Swift




Machine Learning Professional Training


Freshers and Career Changers


Both Classroom and Online Classes


Week Days and Week Ends

Duration :

60 Days

Machine Learning What will you learn?

•Basic to Advance concepts of Machine Learning
•Master Machine Learning concepts from the ground up
•Learn how to use loop statement in Machine Learning.
•Learn about each and every major Machine Learning component.
•Write Compile and Run codes and apps using Machine Learning.
•Learn Machine Learning For Beginners. The Complete Course With Practical Examples
•Students will learn the core concept of making Real Life Project
•Understand Machine Learning and how to use it to write styles programmatically in Machine Learning.
•Learn Machine Learning Complete Course with Professionals from Scratch and Become a Pro in Machine Learning

machine learning and artificial intelligence using swift Training Features

•24 × 7 = 365 days supportive faculty
•Course delivery through industry experts
•Doubt clarification in class and after class
•Online Training with 100% placement assistance
•We Also provide Case studies for Online Training Courses
•Project manager can be assigned to track candidates’ performance
•Make aware of code competence in building extensive range of applications using Python
•Very in depth course material with Real Time Scenarios for each topic with its Solutions for Online Trainings.

Who are eligible for Machine Learning

•Big Data, E-commerce, Cloud Computing, Sap, Erp, Application Programming, Web Development
•Java Developer, Php Mysql, Zend 2.0, java j2ee struts hibernate spring, iOS, Android, html
•Java, Net, C#, Manual Testing, Automation Testing, Manual Testing With Healthcare, Android And Ios Developer
•QA Engineers, C++ Developers, Dot Net Developers, Mac Os Developers, Project Manager, Java Developers, Android Developers, IOS Developers
•Software Developer, IBM MDM, QA, Business Anlaysit, Business Analyst, Software Engineer, Java, Informatica, DataStage, Project Mangement


•Exercise Files
•Credit: Practical Artificial Intelligence with Swift
•Resource: Practical Artificial Intelligence with Swift
•Machine Learning and Artificial Intelligence
•What is Artificial Intelligence?
•What is Machine Learning?
•Why Swift?
•Why Machine Learning and AI?
•On-Device Machine Learning vs Remote Machine Learning
•What is Deep Learning?
•Resources: Neural Networks
•Image Classification – Preexisting Models
•What is Image Classification?
•Downloading Preexisting Machine Learning Model
•Integrating Model in iOS App
•Performing and Displaying Image Classification
•Optional: Displaying Classification Details
•Image Classification – Training Models
•What we will be building?
•Understanding the Steps
•Downloading the Dataset
•Training Model Using CreateML
•What is Vision Framework?
•Implementing Vision Classifier
•Implementing the Classify Function for Vision Classifier
•Performing Image Classification and Displaying Results
•Downloading and Structuring the Dataset
•Training Sound Classification Using Create ML
•Integrating Sound Classifier with iOS App
•Resource: Sound Classification Using Turi Create
•Face Detection
•What is Face Detection?
•Detecting Number of Faces in an Image
•Highlighting Faces Using Face Detection
•Recognizing Facial Landmarks Using Vision
•Text and Barcode Detection
•What is Text and Barcode Detection?
•Implementing Text Detection
•Implementing Barcode Detection
•Resource: Generating Barcodes
•Image Classification Using Turicreate
•Downloading and Setting Up Python Using Anaconda
•Understanding the Dataset
•Implementing Python Script for Downloading Images
•Training Model Using Turi Create
•Integrating Model with iOS App
•Text and Language
•Understanding Machine Learning and AI in Text and Language
•Language Identification
•Named Entity Recognition
•Assignment – Language Identification Using NSLinguisticTagger
•Solution – Language Identification Using NSLinguisticTagger
•Sentiment Analysis
•What is Sentiment Analysis?
•Performing Data Analysis Using Pandas
•Training Model Using Create ML
•Training Model Using Playgrounds
•Importing Model and Displaying Classification
•Sentiment Analysis – Custom Text Classifiers
•Downloading Dataset
•Training Core ML Model Using Xcode Playgrounds
•Implementing ReviewTagger
•Performing Classification
•Drawing Recognition
•Preparing the Dataset
•Training the Model
•Integrating Model into an App
•Activity Recognition Using Core Motion Framework
•Understanding AI in Motion and Gestures
•Style Transfer Using Turi Create
•What will be building?
•What is Style Transfer?
•Sentence Generation Using GPT2 Model
•Understanding the GPT2 Model
•Downloading the GPT2 and DISTIL Models
•Resource: GPT2 and DISTIL Models
•Questions and Answers Using BERT and DistilBERT
•Understanding the App
•Resources: Downloading the Model
•Recommending Ingredients
•Building Dataset
•Integrating Recommendations Model with iOS App
•Predicting Pricing Using Regression
•What is Regression?
•Resource: Mathematics for Machine Learning : Linear Regression
•Training the Dataset Using Playgrounds
•Training the Dataset Using Create ML
•Resource: Creating a Model from Tabular Data
•Augmented Reality with AI
•What is Augmented Reality?
•Adding MobileNetV2 Model to the App
•Executing and Handling Vision Request
•Process and Display Results
•Next Steps