Gaussian elimination, LU Factorization, subspaces, eigenvalues and eigenvectors, SVD, PCA, and other applications.
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Conditional probability, expectation, variance, joint probability, MLE and CLT, hypothesis testings, and distributions.
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LLN, CLT, confidence interval, moment generating functions, and so on. [Still not finish]
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SLR estimaters and bias, MLR estimaters and bias, ANOVA (Type 1/2/3), model diagonsis and selection, logistic regression.
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Stationary condition, ARMA models, ARIMA models, partial autocorrelation, exponential smoothing techniques, and Prophet.
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Data types, common charts, design principles, basic Matplotlib and Pandas, Stephen Few’s Rules for Color.
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Data pipeline, text processing, TFIDF, computer networks basics, AWS, cookies, APIs, and Selenium.
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Ridge regression, LASSO regression, naive bayes, decision tree, random forest, clustering, and basic pyTorch.
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Recommender system, backpropagation, neural network, AdaBoosting, gradient boosting, and basic NLP.
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PostgreSQL, CRUD, JOIN, indexing, window function, database transaction, and schema refinement.
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Apache Spark, Spark operations, Spark RDD and paired RDD, Spark SQL, and Spark MLlib.
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Python, list comprehensions, set, dictionary, counter, string operations, OS/SYS modules, copies.
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Java, data types, loops, input and output, functions and libraries, object oriented programming.
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Sorting algorithms, walking algorighms, searching algorithms, graph algorithms.
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Multi-process, multi-threads, mutual exclusion, condition variables, EDM, IPC, sync, I/O devices, and RPC.
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RISC assembly, branch prediction, data dependency, Tomasulo's algo, memory ordering, cache and LRU, coherence and consistency.
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IDE, VCS, OOP, UML, Android development, requirement engineering, design patterns, black/white-box testing.
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GDB, PWN, ida, shellcode, stack overflow, and so on. [Still not finish]
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