If you plan to build ChatGPT, go slow. Do not spoil the wonder with haste. Why am I saying this? Well, let us try to learn together.
Certainly we can build an application like ChatGPT.
Especially after learning artificial intelligence, as a project we can start building a language model like ChatGPT.
However, we need to remember a few things before we proceed.
Firstly, building a large language model like ChatGPT is a complex and challenging task.
What kind of challenge waits for us?
To be precise. A lot.
If you are a complete beginner your journey to learn TensorFlow might start from here.
For the TensorFlow beginners we have a dedicated category – TensorFlow for Beginners.
But besides that, you may need to learn several other machine learning and data science libraries.
As a result, you may check these categories as well – NumPy, Pandas, Matplotlib.
However, without learning Python, you cannot learn the usages of these libraries. Why? Because they all use Python as the Programming language.
Therefore please learn Python at the very beginning and start learning TensorFlow.
And, finally please check our Mathematics, Discrete Mathematics and Data Structures categories specially. We have tried to discuss from basic to intermediate level so that you can pick up the core ideas of TensorFlow.
First, we need huge resources, expertise and time.
Second, thinking of the complexity of the task that is waiting for us.
Because we need to learn three things at the same time.
One is natural language processing (NLP).
Another is deep learning.
And the third one is large-scale machine learning techniques.
However, we have not finished yet.
We also need access to large amounts of data to train our model.
Moreover, we need a computing infrastructure to run the training process.
Therefore to start with we can think of a smaller project and go slow to build ChatGPT at the end.
A smaller project will give us necessary experience to develop and build skills and confidence at the same time.
To perform tasks like text generation, text classification, or question-answering requires a lot of dedicated hard work and time.
On top of that it needs skills and experience.
So go slow.
Image by Gerd Altmann from Pixabay
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TensorFlow, Machine Learning, AI and Data Science
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