Clearly marked the goal and objectives. Categorise and select training data and datasets effectively. Choose the right model and architect is necessary. Followed by implementing the model. Evaluate and optimise for best result. Iterate and fine tune for better accuracy. Continuous iteration and tuning till the accuracy of outcome gets closer to 100% is a big job.