Urgent help with introductory AI exam

hello, I'm an computer science engineering undergraduate with experience in building algorithms for deep learning and machine learning. Also i have done some exams in these sbjects in the university. I'm sure i can assist you in this exam and please contact me for more information.

' I AM AVAILABLE TODAY ' Hi there, I have experience of giving machine learning, ai, deep learning exams. I have given intermediate level exams for this topic including theory as well as practical coding in both languages such as python and R programming language. Please open the chat box to discuss further. I assure you exams grade will be awesome. Hope to see you soon Thank you

Hi I have read your job description. Can you please tell me what kind of exam is this? Best.

Hi, I'm an experienced full stack data scientist proficient in AI, Machine learning and data science. I have experience on AI exams. I have done certification courses on Coursera, Udemy and Microsoft websites. I'm available for the day. I can help with your AI exam. Let's connect over chat to discuss more. Regards, Vinod

Greetings, Trust things are safe and fine at your end, I've an over 8+years hands-on experience in AI Industry. In span of my career I've worked for Bloomberg as an AI Scientist. I hold double masters in Artificial Intelligence, Mathematics and Computer Science from Georgia Tecg, I've had helped many students help in their Computers and AI Exam. I'm glad to say that every student I helped has always secured maximum on the tests, I always assure the best results. I would love to help you and assure to complete your exam before time with all the correct answers. Looking forward for the positive synergy. Regards, Vishesh.

Hi, I work on Python for Machine learning and AI. I develop professional python scripts with proper comments at each step. I use pandas python library to serve the purpose. I also work on Numpy, Scipy & Visualization (Matplot & Seaborn). Below is a list of techniques, tools and languages I use. Techniques: Regression, Classification, Clustering K-NN, K-Means SVM, Kernel SVM, Naive Bayes Decision Tree, Random Forest, Feature extraction, Data analysis. Tools and Libraries: Sckit-Learn Scipy Pandas Spyder jupyter Anaconda OpenCv Languages: Python Jupyter Notebook