Pinned Repositories
Activity-Detection-using-IMU-sensor
User activity detection using IMU (Inertial Measurement Unit) sensors and power of deep learning. The accelerometer data from smart wearables is used for continuous activity detection, which can be used for in depth activity monitoring and recommender systems.
ANOVA---Sales-Volume
Analysis of Variance
Correlation_Vapor-Pressure
DCNN-timeseries-RUL
DCNN for Machine RUL Prediction using Time-series Data
Hierarchical-clustering
Identify-Facial-Expression
A step closer to intelligent infotainment - Machines that understand your mood!!..
Manufacturing_Line-i4.0
Shop floor always have challenges. When the part fails at the end of line testing, shop floor manager instinctively retrace your steps to identify at what point you went wrong. Here, the ML based algorithm is closely monitoring the parts as they progress through the manufacturing processes. So that the defective parts can be intelligently identified. An i4.0 use case with machine learning.
NER-Named-Entity-Recognition
Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify named entity mentions in unstructured text into pre-defined categories such as the person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.
Predict_Price_from_Text-NLP-Tensorflow-Case_study
Wide Deep Learning - Wide models are models with sparse feature vectors, or vectors with mostly zero values. Multi-layer deep networks, on the other hand, where there may be unexpected relationships between inputs and outputs. If you have got a prediction task that could benefit from both of these models (recommendation models or models with text inputs are good examples), wide & deep might be a good fit.
Predict_RNA-RNA_Interaction
In this project I have used deep learning methods to predict RNA-RNA interaction (RRI) from the sequencing-based training data.
mohan-mj's Repositories
mohan-mj/DCNN-timeseries-RUL
DCNN for Machine RUL Prediction using Time-series Data
mohan-mj/KNN_K-Nearest-Neighbor
k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression
mohan-mj/NLP-GloVe-Sentiment_Analysis
mohan-mj/K-Means-Clustering
mohan-mj/Random-Forest-Classification
Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes or mean prediction of the individual trees.
mohan-mj/tflite-rock_paper_scissors
mohan-mj/ANN-Bike_Sharing-Boston_Housing
mohan-mj/examples
TensorFlow examples
mohan-mj/Markdown-Pricing
mohan-mj/Typo-Corrector
mohan-mj/ai-on-z-triton-is-examples
This repository contains example samples and Dockerfiles to create inference pipeline using triton inference server on IBM zSystems and LinuxONE.
mohan-mj/angular
The modern web developer’s platform
mohan-mj/data_processing
Use pandas, numpy, matplotlib to process the data
mohan-mj/EDA-projects
mohan-mj/Electrical_Usecases
mohan-mj/Factory_Opt
mohan-mj/FastAPI-The-Complete-Course
mohan-mj/fastapi-zero-to-hero
mohan-mj/gsoc-wav2vec2
GSoC'2021 | TensorFlow implementation of Wav2Vec2
mohan-mj/ibmz-optimized-for-tensorflow
IBM Z Optimized for TensorFlow Documentation and Samples
mohan-mj/low_latency_lstm_forecasting
Repository for credit card fraud detection notebooks and ONNX models
mohan-mj/NLP
mohan-mj/Pandas
mohan-mj/pandas_exercises
Practice your pandas skills!
mohan-mj/poetry_demo
mohan-mj/snapml-examples
IBM Snap ML Examples
mohan-mj/SPARQL-query
mohan-mj/TabFormer
Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)
mohan-mj/Viewers
OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages
mohan-mj/zDataAndAIMeetups
Accelerate Journey to AI on IBM LinuxOne