About Me

Let me tell you a few things...

Eshban Suleman

BIO

I am a Data Science Enthusiast. I love reading and learning about new trends in the fields of AI. I also love to play different sports like Table Tennis, Cricket, Basketball to name a few. I enjoy watching movies and TV series a lot, SciFi is my favorite genre beside fantasy and superheroes. Listening to music is also one of my favorite things to do, actually I do almost all the time. I believe that learning is a never ending process and learning new things is almost like a hobby to me. Now have a look on my skills.

Technicalities

Machine Learning Algorithms

Linear Regression, Logistic Regression, Random Forrest, Decision Trees, Principal Component Analysis, Linear Discriminant Analysis, Naive Bayes, Support Vector Machine, K-Nearest Neighbors, Hierarchical Clustering, Neural Networks

Deep Learning Methodologies

Deep Boltzmann Machine, Deep Belief Network, Multi Layered Perceptron, Convolution Neural Network, Recurrent Neural Networks/ Long-Short Term Memory(LSTMs) Cells, Stacked AutoEncoder, Variational AutoEncoder

Computer Vision Algorithms

SIFT, SURF, Viola-Jones Algorithm, Eigenfaces, Kalman Filter, SSDs, Generative Adversarial Networks

Natural Language Processing Algorithms

Word2Vec, CBOW, Skip-Gram, CNNs, RNNs, LSTMs, GRUs

Big Data

Apache Hadoop, Apache Spark

Machine Learning Libraries

Scikit-Learn for ML Algorithms
NumPy for Mathematical Computation
Pandas for Data Wrangling
Matplotlit/Seaborn for Data Visualization

Deep Learning Frameworks

Tensorflow, PyTorch, MXNet, Keras

Some Other Libraries

OpenCV, NLTK, Gensim, Spacy

Tools

Spyder IDE, Jupyter Notebooks, Google Colab, Tableau for Visualization/Data Mining