Learn AI without any prerequisites
Welcome to KAI Class: An integrated AI learning platform
30 Class Deep Learning
This course is specially designed to teach deep learning to anyone in 30 classes with basic python programming as prerequisite. After this course you will be able to solve all the real world problems using deep learning as we teach you all the mathematics so you can innovate with algorithms
Be in Demand with Our Professional Training
With our specially designed courses made to plan AI careers for everyone
- Research Intern at Axis India Machine Learning Research Labs, Jaipur
- Skills in applying intricate algorithms based on deep-dive statistical analysis and predictive data modeling that were used to deepen the relationships, strengthen longevity and personalize interactions with customers,
- Proficiency in analyzing and processing complex data sets using advanced querying, visualization, and analytics tools.
- Knowledgeable and detail-oriented in utilizing statistical models
- Broad scientific and mathematical knowledge with the ability to apply learning to real-world situations
Presented a research paper titled “Infant Weeping calls decoder using Statistical Feature Extraction and Gaussian Mixture Models” at “The Tenth International Conference on Computing, Communications, and Networking Technologies“ at IIT Kanpur.
In this research, he tried to decode the baby crying voices which can be so helpful for novice parents if they can get why their baby is crying which can save a lot of money and time that they spent at pediatricians.
Presented a research paper titled “Positive and Negative vibe classifier by converting two-dimensional image space into one-dimensional audio space using statistical techniques for feature extraction and deep learning for classifying” at the “Springer conference“ at NIT Kurukshetra, Haryana, India.
This paper describes how to classify negative and positive vibes in images which is based on converting images to audios. Also, this paper describes what features to extract in doing audio classification of these types of audio signals and classifying them using multilayer perceptron with special weight initialization and hyperparameters
Presented a research paper titled “Identifying Depression in a Person Using Speech Signals by Extracting Energy and Statistical Features” at the “IEEE Conference“ at NIT, Bhopal, Madhya Pradesh.
This paper is about identifying depression status in a human with their speech signals using Deep Learning
Dean at Jaipur School Of AI
This is a non-profit agency run by Mr. Siraj Raval. Kushal Sharma manages the community of AI for the Jaipur region and has conducted many pro bono Classes for young Students
Remote Data Scientist, TVMucho, London, UK
Worked as a remote data scientist for TV Mucho for analyzing data on customer behavior.
- Well versed with the ML Problems to the most appropriate ML Algorithms according to the task at hand: Prediction, Classification and Clustering
- Supervised Learning(Classification and Regression) Algorithms and Unsupervised Learning(Clustering and Dimensionality Reduction)
- Deep Learning CNN, RNN, Feed Forward Neural Networks, Generative Adversarial Networks, Variational Autoencoders, good working knowledge of all the tools involved in making statistical inference
- Different metrics involved in descriptive Univariate and Multivariate statistics
- Frequentist Inference(Hypothesis Testing, ANNOVA)
- Complete Knowledge of Python with Pandas, Numpy, Scikit Learn, Tensorflow, Keras, Scipy, PyTorch and can code all the ML algorithms without any pre-written python module
- Data Pre-processing and Data Mining
- Matrix Algebra(Singular and Non-Singular Matrices, Orthogonal Matrices, Inverse of a Matrix, Positive Definite Matrices and Negative Definite Matrices
- Audio and Image Processing, Feature Extraction, Image/Signal Processing
- Image Processing basic and advanced algorithms such as SIFT, SURF, Edge Detection, Hough Transformation(Line/Generalized), Dithering, Histogram Equalization