Convert frozen graph into tflite file

I have extensive experience in the domains of Natural Language Processing, Recommender Systems,Machine learning, Deep Learning, Computer Vision, and Reinforcement Learning. While working in the domains mentioned above, I have worked used frameworks like TensorFlow, Scikit-learn, PyTorch,STP and UDP, Caffe2, OpenCV, Keras, matplotlib, seaborn, fastai, Pycharm,NILM algorithms etc) I am also very familiar with classification and clustering algorithms such as SVM,FHMM, Combinatorial Optimization, HART 85 Algorithm, Maximum Likelihood Estimation, KNN, LDA, Fuzzy classification I’m honest, creative and a unique person to carry out your tasks given to me. Leaving your project on our hand is a privileged; we'll make sure that the project is done in a perfect way and do our best until you satisfied. I would love to discuss this project with you and meet your exact requirements. I am confident I can provide you with top notch materials that will fit your needs. I'm proud my work on being professional, of the highest quality and always delivered on time. you can hire me directly through this link https://www.freelancer.com/u/olaideejiwole

Dear Hiring Manager. My interests are machine learning, computer vision, natural language processing, unsupervised learning, and deep learning. I have very good experience in C++, Opencv, Python, numpy, Tensorflow and Torch7. I have worked on many research & industrial projects related to machine learning field. I also have good research experience that allow me to understand and implement state-of-art machine learning models and use it for new applications. I also love problem solving and participated in Arab Collegiate Programming Contest, 2013. I solved over 86 problems in UVA, Codeforces, and SPOJ. I have studied many important topics in ML and NLP through online courses such that (CS229 Stanford University, by Prof. Andrew Ng), but the topics that I have covered theoretically and practically are: linear regression and logistic regression, locally weighted linear Regression, PCA, distribution fitting, neural network and backpropagation algorithm, deep learning and unsupervised feature learning, autoencoders, convolutional neural network (ConvNet), dropout regularization technique, K means, linear SVM, gaussian mixture model and Gaussian process. I am looking forward to your response. Thanks.

I am working on deep learning since last 2 year and Tensorflow lite it's lighter version we need to quantize model so it's able to run on mobile and embedded devices. let me know your requirements so that i can provide you more details on that.