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Evaluation.\u003c/li\u003e\n\u003cli\u003eRNNs and LSTMs Models for Time Series-\u003e Preprocessing, Training, Inference and Evaluation.(Beta)\u003c/li\u003e\n\u003cli\u003eCNNs for Image Processing-\u003e Preprocessing, Training, Inference and Evaluation.(Beta)\u003c/li\u003e\n\u003cli\u003eGANs for Generative models.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch4\u003eActivation functions implemented\u003c/h4\u003e\n\n\u003cul\u003e\n\u003cli\u003eReLU\u003c/li\u003e\n\u003cli\u003eLeaky ReLU\u003c/li\u003e\n\u003cli\u003eSigmoid\u003c/li\u003e\n\u003cli\u003eSoftmax\u003c/li\u003e\n\u003cli\u003eTanh\u003c/li\u003e\n\u003c/ul\u003e\n\n\u003ch4\u003eLoss Evaluation Functions\u003c/h4\u003e\n\u003cul\u003e\n\u003cli\u003eCross Entropy Loss\u003c/li\u003e\n\u003cli\u003eMean Sqaure Error\u003c/li\u003e\n\u003c/ul\u003e\n\n\u003ch3\u003eGoals for the future update versions..\u003c/h3\u003e\n\u003cul\u003e\n\u003cli\u003eMore Models are to be implemented like CNNs, RNNs, LSTMs, GANs, 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