Data Science, Deep Learning and Machine Learning with Python

The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. We'll cover the machine learning, AI, and data mining techniques real employers are looking for, including: Deep Learning / Neural Networks (MLP's, CNN's, RNN's) with TensorFlow and Keras + Sentiment analysis + Image recognition and classification + Regression analysis + K-Means Clustering + Principal Component Analysis + Train/Test and cross validation + Bayesian Methods + Decision Trees and Random Forests + Multivariate Regression + Multi-Level Models + Support Vector Machines + Reinforcement Learning + Collaborative Filtering + K-Nearest Neighbor + Bias/Variance Tradeoff + Ensemble Learning + Term Frequency / Inverse Document Frequency + Experimental Design and A/B Tests.

Data Science, Deep Learning and Machine Learning with Python

... Engineering is an interesting and vast field. New technologies are discovered or invented every day, and the older ones must get updated In the past, engineers used to search libraries or go through various books to keep up with the recent technological advancements or find the solution to various problems. Nowadays, it is possible to do so with the help of just one click.

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