Welcome to the Complete Deep Learning Course 2021 With 7+ Real Projects This course will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand. Other courses and tutorials have tended to stay away from pure TensorFlow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning!This course is designed to balance theory and practical implementation, with complete google colab and Jupiter notebook guides of code and easy to reference slides and notes. We also have plenty of exercises to test your new skills along the way!This course covers a variety of topics, including Deep Learning.Google Colab Anaconda Jupiter Notebook Activation Function.Keras.Pandas.Seaborn.Feature scaling.Matplotlib.Scikit-Learn Sigmoid Function.Tanh Function.ReLU Function.Leaky Relu Function.Exponential Linear Unit Function.Swish function.Corpora.NLTK.TensorFlow 2.0Tokenization.Spacy.PoS tagging.NER.Stemming and lemmatization.Semantics and topic modelling.Sentiment analysis techniques.Lexicon-based methods.Rule-based methods.Statistical methods.Machine learning methods.</
Build on your existing knowledge with intermediate machine learning techniques and real-world applications.
Build on your existing knowledge with intermediate tensorflow techniques and real-world applications.
Build on your existing knowledge with intermediate deep learning techniques and real-world applications.
Build on your existing knowledge with intermediate data science techniques and real-world applications.
Master TensorFlow for building and deploying deep learning models. From basics to production-ready applications.
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