Machine Learning to carry out matching of resumes and job orders

Hi, I have experience using R for data analysis as well as recommendation engines. I have built a prototype job and candidate recommendation engine quite similar to the project you describe. I would be happy to demo it to you. To improve accuracy, I would look at building a number of models using different algorithms and creating an ensemble model. Regards, Chris

I have a working resume parser with me. Tested on various formats like .pdf, .html, .docx so, that will be the good start. Coming to your questions: 1) Methodology: Naive bayes to start with. We can rank resumes for a given rank based on their required set of skills. 2) If you can provide a tagged dataset of few resumes it would be great. I can develop a supervised learning method to perform the task. 3) It will be finished in a week if you are looking for a moderately accurate system.

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I have already delivered same type of project "resume-posting matching model". I have nearly 2 years experience in this domain. let us discuss your project requirements and cost as per your requirement.

I did some same project on my second year and have a lot of experience with NLP, ML and neural networks. I think your work is a already implemented in industry so exactness will be confirmed

I have done my final year project Handwriting recognition using Machine Learning algorithms. I was able to do the project well handling large amount of training set. I used both Python and Matlab. Having strong exposure to both Machine Learning and python I feel that I would be able to take up the project.

I will develop this

I am a creative, flexible and focused individual who is interested in Data Science, Machine learning, Deep learning, Natural language processing, Big Data, Image processing and entire Analytics space. I have acquired knowledge of Python programming. I have exposure to COMPUTING SKILLS Programming Languages: C, Java, Python Machine learning: Logistic Regression, Decision Trees, Linear Regression, Neural Networks, SVM, Naive Bayes, K-means, Random Forest… Deep Learning: Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks... Big Data: HDFS, MapReduce, Spark, Hive, Flume, Pig, Sqoop, Hbase, Kafka, Oozie, ZooKeeper, Mahout... Natural Language Processing: Nltk toolkit. Digital Image Processing: OpenCV. PROJECTS I have experience in working various projects related to Machine Learning and Deep learning. I am good at explaining complicated ideas. I am a part of a fair number of projects, for example: Object detection from dynamic viewpoint: Object detection from the dynamic viewpoint is a Machine learning and Deep learning based project where the trained system can detect the objects like cars, buses etc. from the dynamic viewpoint like moving the camera or a drone camera. Advanced topics of Machine learning/Deep learning like Convolutional Neural Networks (for image detection) and Recurrent Neural Networks along with Long Short-Term Memory (for caption generation)