Welcome to my Machine Learning notes
I am Ikram Ali, I specialize in building ML engineering and data science teams from the ground up. My current passion is NLP and MLOps
I approach my career by purposefully building domain knowledge in all the cross-functional disciplines required to deliver successful Data Science projects. This includes Research, Data Engineering, Machine Learning Engineering, Management, as well as dabbling in Agile Program Management and Product Management within other roles. This allows me to lead cross-functional teams and know the pain points of bringing a model from ideation to production. For further information regarding my credentials, please refer to my LinkedIn and Github profiles
I would like to offer concise definitions and comprehensible explanations of Machine Learning and Deep Learning.
ml_notation.ipynb
probability/what_is_probability probability/conditional_probability_and_bayes_theorem probability/random_variable probability/discrete_distributions probability/continuous_distributions probability/joint_distributions probability/covariance_and_correlation probability/estimators_and_sampling_distributions probability/moments_generating_functions probability/maximum_likelihood_estimation probability/confidence_interval probability/hypothesis_testing
calculus/intro calculus/derivatives
algebra/intro
deep_learning/what_is_deep_learning deep_learning/tensor deep_learning/loss_functions deep_learning/evaluation_metrics
linear_algebra statistics
algorithms/sorting.md algorithms/graphs.md algorithms/trees.md algorithms/shortest_path.md algorithms/greedy_algorithms.md
graph/introduction graph/graph_neural_networks graph/graph_equations
torch/pytorch_fundamental.ipynb torch/pytorch_workflow.ipynb torch/pytorch_neural_network_classification.ipynb torch/pytorch_transformers.ipynb
recommend/introduction.ipynb recommend/matrix_factorization.ipynb
practise/probability_solutions.rst practise/R_solutions.rst
genindexmodindexsearch