Tag Archives: ai
Job Description – Chief Artificial Intelligence (AI) Officer
Whether your organization needs a chief artificial intelligence (AI) officer is a topic where there have been differences of opinions. However, the primary idea is to have someone who heads or leads the AI initiatives across the organization. The designation could be chief AI officer, Vice-president (VP) – AI research, Chief Analytics Officer, Chief Data Officer, AI COE Head or maybe, Chief Data Scientist etc. One must understand that building AI/machine learning models and deploying them in production is just one part of the whole story. Aspects related to AI governance (ethical AI), automation of AI/ML pipeline, infrastructure management vis-a-vis usage of cloud services, unique project implementation methodologies etc., become of prime importance once you are done with the hiring of data scientists for …
Bias Detection in Machine Learning Models using FairML
Detecting bias in machine learning model has become of great importance in recent times. Bias in the machine learning model is about the model making predictions which tend to place certain privileged groups at a systematic advantage and certain unprivileged groups at a systematic disadvantage. And, the primary reason for unwanted bias is the presence of biases in the training data, due to either prejudice in labels or under-sampling/over-sampling of data. Especially, in banking & finance and insurance industry, customers/partners and regulators are asking the tough questions to businesses regarding the initiatives taken by them to avoid and detect bias. Take an example of the system using a machine learning model to …
Security Attacks Analysis of Machine Learning Models
Have you wondered around what would it be like to have your machine learning (ML) models come under security attack? In other words, your machine learning models get hacked. Have you thought through how to check/monitor security attacks on your AI models? As a data scientist/machine learning researcher, it would be good to know some of the scenarios related to security/hacking attacks on ML models. In this post, you would learn about some of the following aspects related to security attacks (hacking) on machine learning models. Examples of Security Attacks on ML Models Hacking machine learning (ML) models means…? Different types of Security Attacks Monitoring security attacks Examples of Security Attacks on ML Models Most of …
JupyterLab & Jupyter Notebook Cheat Sheet Commands
Are you starting to create machine learning models (using python programming) using JupyterLab or Jupyter Notebook? This post list down some commands which are found to be very useful while one (beginner data scientist) is getting started with using JupyterLab notebook for building machine learning models. Notebook Operations: The following command helps to perform operations with the notebook. Ctrl + S: Save the notebook Ctrl + Q: Close the notebook Enter: While on any cell, you want to enter edit mode, press Enter. Cells Operation: The following commands help with performing operations on cells: J: Select the cell below the current cell; This command would be used to go through cells below the …
Missing Data Imputation Techniques in Machine Learning
Have you come across the problem of handling missing data/values for respective features in machine learning (ML) models during prediction time? This is different from handling missing data for features during training/testing phase of ML models. Data scientists are expected to come up with an appropriate strategy to handle missing data during, both, model training/testing phase and also model prediction time (runtime). In this post, you will learn about some of the following imputation techniques which could be used to replace missing data with appropriate values during model prediction time. Validate input data before feeding into ML model; Discard data instances with missing values Predicted value imputation Distribution-based imputation Unique value imputation Reduced feature models Below is the diagram …
Code of Ethics in Artificial Intelligence (AI) – Key Traits
Do you know that organizations have started paying attention to whether AI/machine learning (ML) models are doing unbiased, safe and trustable predictions based on ethical principles? Have you thought through consequences if AI/machine learning (ML) models you created for your clients make predictions which are biased towards a class of customer, thus, hurting other customers? Have you imagined scenarios in which customers blame your organization of benefitting a section of customers (preferably their competitors), thus, filing a case against your organization and bring bad names and loss to your business? Have you imagined the scenarios when ML models start making incorrect predictions which could result in loss of business? If above …
AI & RPA to Automate the Talent Acquisition Processes
Artificial Intelligence (AI) is not only finding its usage in almost all the existing business processes but also, enabling business stakeholders and entrepreneurs to think of innovative ideas to come up with new business processes and gain competitive advantage. Robotic Process Automation (RPA) makes use of AI to make intelligent decisions and automate end-to-end business processes to achieve human-like efficiency and effectiveness, thereby, augmenting humans to be more productive and achieve more in less time. Talent acquisition is a business domain where there are many business processes which are repetitive in nature and could make use of AI for business process automation and achieve the goal of greater efficiency and scale. …
8 Machine Learning Javascript Frameworks to Explore
Javascript developers tend to look out for Javascript frameworks which can be used to train machine learning models based on different machine learning algorithms. The following are some of the machine learning algorithms using which models can be trained using different javascript frameworks listed in this article: Simple linear regression Multi-variate linrear regression Logistic regression Naive-bayesian K-nearest neighbour (KNN) K-means Support vector machine (SVM) Random forest Decision tree Feedforward neural network Deep learning network In this post, you will learn about different Javascsript framework for machine learning. They are some of the following: Deeplearn.js Propel ConvNetJS ML-JS KerasJS STDLib Limdu.js Brain.js DeepLearn.js Deeplearn.js is an open-source machine learning Javascript library …
How to Create Java NLP Apps using Google NLP API
Natural language processing (NLP) is an AI-based technology which is used for creating apps related to speech recognition, natural-language understanding, and natural-language generation. Some of the applications related to NLP are content classification, sentiment analysis, syntactic analysis etc. In this post, you will learn about how to get set up with a development environment for creating NLP based apps using Google Cloud NLP APIs. Setup Eclipse-based Development Environment for Google NLP API The steps below would help you get setup with Eclipse IDE and Java-based development environment for developing apps using Google Cloud Natural Language API. Create Google Project: Create a project by logging into Google Cloud console. I created …
Quick Introduction to Smoothing Techniques for Language Models
Smoothing techniques in NLP are used to address scenarios related to determining probability / likelihood estimate of a sequence of words (say, a sentence) occuring together when one or more words individually (unigram) or N-grams such as bigram([latex]w_{i}[/latex]/[latex]w_{i-1}[/latex]) or trigram ([latex]w_{i}[/latex]/[latex]w_{i-1}w_{i-2}[/latex]) in the given set have never occured in the past. In this post, you will go through a quick introduction to various different smoothing techniques used in NLP in addition to related formulas and examples. The following is the list of some of the smoothing techniques: Laplace smoothing: Another name for Laplace smoothing technique is add one smoothing. Additive smoothing Good-turing smoothing Kneser-Ney smoothing Katz smoothing Church and Gale Smoothing …
Top 10 Startups Building Speech-to-text Conversion Solutions
This is a list of 10 startups which are using speech recognition technology (Speech-to-text Conversion) to solve different problems. Startup Name What they are doing Behavioral Signals Building emotion recognition and behavioral analytics technology; They are speech-to-text conversion with AI to create powerful predictions. SpeakSee Makes conversations visual and easy to hear for the deaf and hard-of-hearing; It may require integration with Cloud Speech API integration to get real time transcription. HelixAI Helps scientists, researchers, and lab technicians access information and reference data simply using their voice; Spitch Swiss-based provider of solutions in Automatic Speech Recognition (ASR), Voice Biometrics, Voice User Interfaces (VUI), and natural language voice data analytics. The …
How to Build Liv.ai like Speech-to-text Conversion Platform
This article explores the technology landscape which can be used to build similar platform / service offerings like Liv.ai. First and foremost, congratulations to Liv.ai team for leveraging existing cloud-based AI and speech recognition (Speech-to-text conversion) technologies to come up with a set of business offerings which leverages speech-to-text conversion technology to create great value for businesses. The founding team (IIT KGP Alumni – Subodh Kumar, Sanjeev Kumar and Kishore Mundra) nailed it! Doing right thing at right time at right place. Liv.ai enables developers to convert speech-to-text by using Powerful Neural Network Models with exceptional accuracy and minimal latency. At this point, the platform supports 9 languages including Hindi, English, Bengali, Gujarati, Telugu, Tamil, Marathi, …
CareNGrow powers Preventive Healthcare Platform with AI & Cloud-Computing
CareNGrow is building a preventive healthcare platform based on AI and cloud-computing technologies. One of the goals is creating and monitoring the physical, psychological, and behavioural health profile of children in schools. The following represents key workflow steps which is implemented while examining a kid / child: Data gathering Transfer data over internet to cloud Feed the data into the analytics platform Perform the data analysis (Predictive Analytics) Generate health reports This is a brainchild of a young doctor, Dr. Meghana Kambham. CareNGrow is already making waves in different startup competitions owing to the work they have been doing. In this relation, they have been announced as one of the UberExchange winners. Check …
Proscia uses AI-powered Digital Pathology for Cancer Screening
Proscia, a cloud-based digital pathology provider is on a mission to bring computer intelligence (using artificial intelligence (AI)) to pathology, fighting cancer by unlocking the data hidden in tissue. The following are some of the key aspects of cloud-based digital pathology technology of Proscia: Telepathology Data management Pathology Cloud Web application for managing/sharing slides’ images Image analysis (AI) The details in relation to Proscia technology can be found on this page, Proscia Platform. Proscia Technology – Telepathology One of the key aspects of the Proscia platform is data gathering (slides’ images) from different diagnostic sources. In order to achieve this, Proscia platform supports following: Supports different slide scanning hardware devices to scan the slides and create related …
Niramai uses AI / Thermal Imaging for Breast Cancer Screening
Niramai Health Analytix, a Bengaluru-based startup is creating an AI-powered software system for breast cancer screening. Niramai is using following technologies to achieve the objective of breast cancer screening: Thermal image processing using thermal sensing device (thermal camera) Machine learning algorithm Hardware devices integrated with real-time cloud-based diagnostics; These hardware devices are capable of capturing thermal images What/How of Thermal Image Processing? Thermal image processing, also termed as thermal imaging, is a method of improving visibility of objects in a dark environment by detecting the objects’ infrared radiation and creating an image based on that information. source: techtarget. The key to capturing thermal images of an object is a heat sensor (also called as thermal camera) which is …
AIndra uses AI to Solve Cervical Carcinoma Cancer
AIndra, a Bengaluru-based startup is into the business of building innovative products and technologies to aid computational pathology. Established in 2014, AIndra’s vision is to build state of the art medical devices for screening Cervical Carcinoma. This article is created solely based on my analysis of information found on AIndra’s website. The objective is to make readers aware of some of the following technologies AIndra is using and, how they can be used to solve healthcare problems, in general. The goal is provide food for thought to the readers such that they can use some of these technologies in their future startups. Computation Pathology Telepathology If you work in AIndra, please feel …
I found it very helpful. However the differences are not too understandable for me