POC on Database log to predict failure/anomaly.

Hi I am a very experienced statistician, data scientist and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, PYTHON, WEKA, TABLEAU, POWER BI, and EXCEL tools like machine learning, deep learning, AI, NLP, hypothesis testing, forecasting, T-test, ANOVA etc. Looking forward to discussion, Best Regards, Suyash

Dear sir. Your project attracted my attention at first glance, because I've extensive experience in this field. I'm really confident about your project, and very eager to join your project. If we have a chance to cooperate, I'll do my best to provide wonderful result. Looking forward to your response. Best Regards.

Data Scientist Big Data Expert Many years of experience in - machine learning - deep learning - RNN, LSTM, CNN - Computer Vision, NLP - statistics - Big Data Tools: - Colab - AWS - GCP - Hadoop Stack Languages: R Python JAVA Frameworks: Tensorflow Keras Radish Big Data Components: Kafka Spark Flink Prometheus Grafana Well updated about the current Industry trends and State of the art approaches

I am machine learning researcher. I have expertise in Computer Vision, NLP, & Machine Learning algorithms. # In Computer Vision, I implemented models like 1. Image classification 2. Object Detection 3. Image segmentation 4. Image enhancement & restoration 5. Video classification and Compression. # In NLP, I worked on 1. Text Classification 2. Sentiment analysis 3. Neural machine translation 4. Text summarisation 5. Entity Extraction # Dataset I have worked on 1. Medical image 2. Solar energy 3. Satellites and IR sensor data 4 Text 5 Images # Framework I am familiar to: 1. Tensorflow 2. Keras 3. Scikit learn 4. Pytorch 5. Numpy 6. Pandas 7. Xgboost/catboost 8. OpenCV # Neural networks architecture I have implemented, 1. CNN 2. LSTM/RNN/GRU 3. TRANSFORMER 4. GAN & it's Variants # Popular architecture I have worked on: 1. Alexnet 2. Resnet 4. Mobilenet 5. Faster RCNN & it's variants 6. DEEPLAB & it's variant 7. YOLO 9. Auto encoder # programming language 1. Python 2. Java 3. C++