Jay Parmar Email & Phone Number

While working I came across this part of the world that is AI which caught my eye and made me challenge myself and be relevant to my soft skills. As my work involved client interaction and inspecting technical work, the AI world requires technical as well as non-technical skills which I found to fit my profile. The first language that I was exposed to was SQL which stands for Structured Query Language. SQL consists of 4 sublanguage commands that is DQL, DDL, DML, and DCL. I have a good hands-on and project experience in SQL where I have created, manipulated and retrieved data. The language that I was more curious to learn was Python and the moment I started learning about it it became more and more interesting. I started it with simple coding and then challenged myself by increasing the level of problem statement. We were taught concepts from Machine Learning and Deep Learning. Linear Regression, Logistic Regression, Decision Tree, Random Forest, XGBoost, SVM, LDA and Naïve Bayes these are the supervised learning algorithms that were taught. I have gained hands-on and project experience in Regression as well as in Classification problems. Ever wondered how big companies like Netflix, Myntra, Amazon recommend you their products based on your purchase history, this is how they do it by using Unsupervised learning methods like PCA, Clustering, SVD, and Association Rule mining. The challenge didn’t end here it had just started and it was time for Deep Learning. Neural Networks are the algorithms which send and receive signals from one neuron to another for transferring information just like human brain. I have always wondered how our handset is grouping images with similar faces. And the idea behind this technology is CNN i.e. Convolutional Neural Network. A was developed which classifies images and additionally have applied Pretrained model VGG16 for the same purpose.Many people nowadays are using ChatGPT for various purpose and it works on a concept called NLP Natural Language Processing. There are various algorithms in NLP such as RNN, LSTM, Bidirectional LSTM, Transformers. I had created an algorithm for classifying tweets and customer feedback into two categories positive and negative. This method will save a lot of time and help in reviewing negative feedbacks.With the help of PowerBI I was able to make Dashboards consisting of charts such as bar chart, columns chart, scatter chart, etc. for making data interactive and saves time in case of decision making.