Deep Learning with DataCamp and Twitter13 Dec 2021 / 2 minutes to read Elena Daehnhardt |
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While having some machine learning experience of working with Scikit Learn, I was always interested in Deep Learning. The plan is to learn basic concepts and apply algorithms to a real-life situation, which I have always liked. I have found a DataCamp course, the Introduction to Deep Learning in Python as part of the Deep Learning in Python track.
The Introduction to Deep Learning in Python provides the fundamentals to understand Deep Learning and how neural networks are created in Keras. The course is easy to follow. The most challenging concept explained in the course is the backpropagation method applied to minimise the prediction error while adjusting network weights. The programming exercises are easy to follow and have an excellent interface for running the Python code.
To cope with possible delays in this process, I decided to share my process on Twitter. I post on Twitter the main things I learned in this course and retweet helpful visuals I found in my Twitter network. I have found out that the data science on Twitter is very supportive and sharing for newcomers like me. There is also a pretty helpful hashtag #66DaysOfData, which motivates me to continue.
Overall, it is possible to complete the course in just four hours, but I took more time to deal with other commitments. In the end of the Introduction to Deep Learning in Python course I have got the certificate. By the way, I am working on the course summary post, and it will contain a bit of coding. Stay tuned, and thanks for reading!
Next, I have completed the Introduction to TensorFlow.
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About Elena Elena, a PhD in Computer Science, simplifies AI concepts and helps you use machine learning.
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