In this talk, we will present all the required tools for an end to end project in artificial intelligence and machine learning with a focus on Natural language processing.
Starting from:
– Environment: The step-up needed to start.
– Data processing: Processing and converting raw data to a usable one.
– Prototyping: Creating, selecting, and fine-tuning a model.
– Deploying: Serving the resulted model to be used.
We selected these tools having these reasons in mind:
– Efficiency: Is the tool covers the most utilities needed for the specific step.
– Productivity: Is the tool respecting the “don’t repeat yourself” and “don’t reinvent the wheel” principles, and you can do the maximum with the minimum.
– Ease and Control: The tools that are needed to manage the pipeline and write code.
Who may be interested:
– Machine learning engineers/Data scientists.
– Anyone experimenting with code in an iterative process.
– Anyone working with data.
