Given clinical parameters about the patient, we can predict whether they have heart disease or not.
-
Comprehensible classification models: a position paper: ACM SIGKDD Explorations Newsletter: Vol 15, No 1 (no date). Available at: https://dl.acm.org/doi/abs/10.1145/2594473.2594475 (Accessed: 10 March 2022).
-
Data Cleaning: Detecting, Diagnosing, and Editing Data Abnormalities (no date). Available at: https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020267 (Accessed: 14 March 2022).
-
Roßbach, D.P. (no date) ‘Neural Networks vs. Random Forests – Does it always have to be Deep Learning?’, p. 8.
EDA and Plotting: RStudio, Tableau, Tensorflow, numpy, pandas, matplotlib, seaborn.
Models: LogisticRegression, KNN, RandomForestClassifier, OneHotEncoder, LabelEncoder.
Model Evaluators: train_test_split, cross_val_score, confusion_matrix, classification_report, precision_score, recall_score, f1_score, plot_roc_curve, accuracy_score.
Keras for Deep Learnng: Sequential, Dense, LeakyReLU, PReLU, ELU, Dropout, StandardScaler, train_test_split, confusion_matrix, accuracy_score.
I have experience as a data scientist and machine learning engineer. I have worked on projects involving the development of predictive models, the optimization of machine learning algorithms, and the deployment of machine learning models. I have also worked on projects involving the analysis of large datasets, the development of data-driven insights, and the creation of data visualizations.
Data Exploration and Visualization, Neural Network and Deep Learning, Model Evaluation and Analysis, TensorFlow 2.0, NumPy, Scikit Learn, Transfer Learning, Image recognition and classification, Matplotlib, supervise Learning: Classification, Regression and Time Series, Decision Trees and Random Forest, Ensemble Learning, Hyperparameter Tuning, Pandas, Kera’s, Regression Analysis, Hadoop, Apache Spark, Kafka, and Apache Flink, GPU with Google Collab, Python, R, HTML, CSS, Node.js, JavaScript, Tableau, Power BI, HTML, CSS, Bootstrap 4, JavaScript ES6, DOM, JQUERY, Unix Command-Line, Node.js, Express.js with Node.js, APIs, Git, GitHub and Version control, EJS, Database- SQL, Mongo DB, Mongoose, Authentication and Security, react.js