Today's topic is about self care! I got this book yesterday and I finished it within less than 5 hours. Why? What made it so interesting? What did I learn from it?

![ "Screenshot 2021-10-21 at 16.52.51.png"](https://images.hive.blog/DQmSEUgpFAM8PdNNyKhm1dz7i8M9ipsNJiKHJdCxKECvdkJ/Screenshot%202021-10-21%20at%2016.52.51.png)

We are constantly talking about taking care of our mental health, and I am pretty sure most of us are trying out best practices on a daily basis: like doing sports, relaxation, mindfulness, socializing, etc. However, have you ever thought about the fact that you are in a constant conversation with yourself almost 24/7? **When you wake up, you talk to yourself. Throughout the day, you talk to yourself. Before going to bed, you also talk to yourself.**

We use words to communicate actions or thoughts to our brain, but we don't really use them often to heal it. We appreciate compliments from beloveds like 'I love you', 'you look great', 'you are doing so well'... so why we don't say that to ourselves?

This might not be the most technical book for future Data Scientist/Machine Learning Engineer, but it does teach you a lesson on how to simply use words to mantain a good mental health state, which we will all need when times of high competitiveness and fast growth. 

A lot of us are quiting the most well-paid positions out there. Yes, most people in the field of AI spend at least 1-2 hours looking for a new job. This is pretty sad, and a lot has to do with motivation and mental health. 

The main reason that it is stated for this unfulfillment is the fact that the job does not meet their expectations. I agree with this to some extent. For me, what impacts the most my day to day is the lack of infrastructure and guidance from leaders. The immidiate outcome of this is practitioiners blaming themselves instead of acknowledging a business failure. 

I think it was a beautiful read and it was extremely inspiring 💡 

What do you think is the best medicine for a good mental health? For me - talk to yourself and celebrate achievments.

###### References

[How machine learning creates new professions - and problems](https://www.ft.com/content/49e81ebe-cbc3-11e7-8536-d321d0d897a3)