Ashish jindal data_science_2018_resume
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Dear Connections, I am looking for a job in Computer Vision/AI/ML in Bangalore. I have 1 year of industry experience in Computer Vision and Machine learning and have worked in classification, object detection, and segmentation. With that said I'm open-minded if presented with the right opportunity. I am sharing my CV with you all. Kindly spare some time and refer my candidature to your connections you find suitable to help me. Please be open to share my post. Thank You
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本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Your Guide To Finding The Perfect Part-Time Job
Part-time workers account for a significant part of the workforce, including individuals of all ages. A lot of industries hire part-time workers in different capacities, including temporary or seasonal openings, ranging from managerial to entry-level positions. However, many people still doubt taking on these roles and wonder how a temporary part-time job can help them achieve their long-term goals.
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Ashish jindal data_science_2018_resume
- 1. PERSONAL INFORMATION +91 8107259905 ashishjindal1997@gmail.com ϩ linkedin.com/in/ashish-jindal-97b993114/ Ϯ github.com/Ashish1997 CERTIFICATIONS Machine Learning (Stanford Online, Coursera) Deep Learning (Stanford Online, Coursera) TOOLS/SKILLS Computer vision Deep learning Flask, Django Scikit-learn, Open- CV Keras, Tensorflow HONORS 1000+ score in HackerRank Organised games during college fest STRENGHTS Self-motivated, Passionate Strong Analytical and Problem-solving skills Autodidact Positive attitude EDUCATION 05.2014 - 06.2018 BK Birla Institute of Engineering and Technology, Pilani Computer Science and Engineering HOBBY Reading about new technology Chess Analysing stock market ASHISH JINDAL Computer Vision Developer A fast learner with technical skills in Machine learning, Computer vision and habitual to work in a fast- paced environment, providing time deliverable. September 2018 - present Artivatic.ai Computer Vision Engineer Where I worked on: Car damage detection using Deep Learning: -Trained an end-to-end image-based car damage detector with 81% accuracy and feedback learning capability for automation in insurance industries. Signature detection and matching: - Trained a generic signature detector which can find signatures on any kind of document (KYC, handwritten) with 91% accuracy using FRCNN and matched those signatures with 94% accuracy using siamese network. Usage base vehicle insurance: -Finding driving behavior of the user (overspeeding, drowsiness, etc) and weather data to make risk profile of the insured user. Document Classifier: - Trained an image-based classifier for 10 types of KYC docs detecting 20 unique parts using FRCNN. Car license plate verification: -Detected and verified the license with Dl image using YOLO, tesseract, and OpenCV. ElastiMap: Mapped multiple formats of insurance claim documents to a master document, imitating a human user using Word2Vec and core NLP concepts Devnagri OCR for a handwritten character (97.77%) accuracy. -A state of the art OCR using ConvNet, used ensemble to blend 4 models to improve the accuracy. PROFILE WORK EXPERIENCE PROJECTS