To build predictive models, data science utilizes sophisticated machine learning algorithm. Tools: Python, SQL,Scikit Learn, PyTorch, TensorFlow, Keras, GitStatistics : Inferential Statistics, Hypothesis Testing, Exploratory Data Analysis, Descriptive Statistics, Inferential StatisticsMathematics: Linear Algebra, Matrices, Probability and Combinatorics, CalculusMachine Learning: Supervised Learning, Unsupervised Learning, Support Vector Machines… Show more To build predictive models, data science utilizes sophisticated machine learning algorithm. Tools: Python, SQL,Scikit Learn, PyTorch, TensorFlow, Keras, GitStatistics : Inferential Statistics, Hypothesis Testing, Exploratory Data Analysis, Descriptive Statistics, Inferential StatisticsMathematics: Linear Algebra, Matrices, Probability and Combinatorics, CalculusMachine Learning: Supervised Learning, Unsupervised Learning, Support Vector Machines, Decision Trees, Random Forest, PCA, Naive Bayes, Linear Regression, Classification, Clustering, Bagging, and BoostingNatural Language Processing: Lexical, Syntactical, and Semantical Processing, Chatbots, Classic NLP.Neural Network and Deep Learning: Information flow in a Neural Network, Training a Neural Network, Gradient Descent, Convolutional Neural Networks, Recurrent Neural Networks, LSTM, GRU, Transfer LearningProbabilistic Graphical Models: Directed and Undirected Models, Inference, Learning, Restricted Boltzmann Machines Reinforcement Learning: Classic RL, Markov Decision Processes, Deep Q-learning Show less

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