TensorFlow Developer Certification Specialization
The certification program consists of a series of courses that cover topics such as TensorFlow basics, data pipelines, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), Sequences and Time Series Prediction.
What I have Learned:
This has been a great journey that has taught me a lot about TensorFlow and its applications in a variety of fields, including computer vision, natural language processing, and time series analysis. These are some of the key things I have learned in each course of this specialization:
• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning:
I learned the basics of TensorFlow and how to use it for machine learning and deep learning. It included learning how to use TensorFlow's core APIs and Keras as well as TensorFlow's Estimator API in order to build and train neural networks. In addition, I learned how to use TensorFlow's visualization tools and how to use the TensorFlow ecosystem.
• Convolutional Neural Networks in TensorFlow
I learned how to use TensorFlow to build and train convolutional neural networks (CNNs). In particular, I learned how to use TensorFlow to build image classification and object detection models. Using convolutional layers, pooling layers, and other components, I learned how to construct powerful image recognition models. I also learned how to use transfer learning to improve model performance and reduce training time.
• Natural Language Processing in TensorFlow
I gained a deep understanding of natural language processing (NLP) concepts and how to use TensorFlow for NLP tasks. My learning centered around using word embeddings to represent words as vectors, using deep learning models to classify text, and using sequence-to-sequence models for machine translation. Additionally, I learned how to use pre-trained models for NLP tasks and how to fine-tune them accordingly.
• Sequences, Time Series, and Prediction:
I learned how to use TensorFlow for time series analysis and prediction. Specifically, I learned how to use recurrent neural networks (RNNs) and LSTMs to build models that can analyze and predict time series data. I also learned to use convolutional neural networks (CNNs) for time series analysis and prediction.
Overall, I am grateful for the knowledge and skills I gained through this program. With this newfound knowledge, I am now equipped to build, train, and deploy complex deep-learning models for a wide range of tasks.