Machine learning Supervised, Unsupervised,Reinforcement learning and have knowledge inBagging, Boosting, Gradient descent, Neuralnetworks algorithms (ANN, GAN, RNN, CNN). Model training, Hyperparameter tuning, EDA &Feature Engineering Data Visualization: Python Libraries: Matplotlib,Seaborn, Tensor flow, Tableau, Power BI,Microsoft Excel, Spark. Python Libraries & usage, Pandas: Slicing dataframe, Merging & Joining, Concatenation, Indexchanging, order by & group by, etc. Numpy: Data type, array creation, indexing /slicing, broadcasting rules, structured arrays, etc. Scikit-learn libraries NLTK : Natural Language Processing Blockchain & Cryptocurrency, Ethereum, SupplyChain Management Used Google Colab, Jupyter, PyCharm IDE Configured Google Analytics 4 Worked in Python, Golang. Java Have good knowledge in Linear Algebra,Probability & Statistics
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