The Bold Winner's Blog

Hi Folks, hope you are fine? Hope everything is okay? If you're bothered about anything, feel free to share it through the comment session, you can do this anonymously, I will surely respond the best way I can. Last month has been pretty rough in Nigeria, the #EndSarz protests really created a very tense atmosphere, but thankfully everything is gradually settling back to normal.  I've really been very busy with a lot this year, and as a result I've not been writing as frequently as I should on this blog, but it's all for good and I pledge to write at moments when I am inspired just like this moment. The thing I want to share now relates deeply to mindset and belief systems. And even though I started this blog mostly writing about staying motivated and all, the truth is that if you don't have a deep rooted brief in God, the creator, it's really hard to just be self-motivated. The more you make yourself available to the Creator, you will find out that you will dev

Lesson 4 Revision Supervised Learning Classification Recall that in classification the outputs are categorical or discrete.  Types of Classification Problems: 1. Classification on Tabular data: where data is in form of rows and columns 2. Classification on Image and Sound data: where training data consists of images or audio sounds 3. Classification on text Data: consists of texts whose categories are known Categories of algorithms are: 1. Two class classification: where the prediction has to be in two categories 2. Multi class classification: where predicted has to generate results having more than 2 categories There are 2 key algorithms for optimizing Multi class logistic regression, they are: 1. Optimization tolerance 2. Regularization weight Optimization tolerance controls when to stop iterations when improvements between iterations are lost. So if the improvements between iterations go below a specified threshold, the algorithm stops and returns the current model. Regularization

  Feature Selection: Helps you answer the question: "What are the features that are most useful for a given model?" One of the reasons we need to apply this is that the number of features in your original dataset may be very very high. Benefits:  Eliminates irrelevant, redundant and highly correlated features  Reduce dimensionality for increased performance. As many ML models do not cope well on data with very large dimensions(many features). We can improve the situation of having too many features through dimensionality reduction. Commonly used techniques are: PCA (Principal Component Analysis) t-SNE (t-Distributed Stochastic Neighboring Entities) Feature embedding Azure ML prebuilt modules: Filter-based feature selection: identify columns in the input dataset that have the greatest predictive power Permutation feature importance: determine the best features to use by computing the feature importance scores ********************* Data Drift Data drift is change in the input d

One of Machine Learning's most important process is model training. This is the process in which we transform data into trained ML models, hence its importance.  Before we train our model, it  is important we master data handling,  data preparation and data management because proper data is is a key ingredient for successful ML models. Issues like high bias, classification problems, poor performance are often related to problems on the data itself. So it's really crucial to feed proper, accurate, clean and high quality data into our machine learning models for training. Model training is a core process in Machine learning that allows us to build, train and check the quality of ML models.  Data wrangling is the process through which we clean data, restructure it and enrich the data to transform it into a format that is much more suitable for the training process of Machine Learning Algorithms. ********* Managing data for machine learning work on Azure needs us to understand 2

Days 10-12 2.25(learning functions):  ML is a process for learning functions and models are specific representations of those functions gotten from training data. Y=f(x) + e Where y is output, x is input, f is function and e is the irreducible error. ML algorithms learn from a target function F that describes the mapping. 2.26: parametric and non-parametric algorithms Based on the size and structure of a function ML algorithms try to learn, they can be classified into parametric and non-parametric. parametric: these algorithms maps into a known functional form. It starts by assuming a  form, then learning its coefficients based on that form. non parametric: these algorithms do not make assumptions regarding the mapping between input and output data, so they are free to learn any functional form from the data. Benefits of parametric functions: simpler to understand, faster, easy interpretation and requires less training data. Disadvantages; it's highly constrained, limited com

Day 5 Learnt about Tabular Data - data simply arranged in tabular format like in an Excel spreadsheet with rows, columns and cells where they intersect. Rows describe a single observation, product or entity Columns describe the properties or features of the item. Column values can be continuous (countable numeric values that can take any value) or discrete(categorical) values which have a limited range and needs to be converted. Cells represent single value in row and column intersection. In machine learning we ultimately work with numbers specifically vectors. So everything that isn't numbers like the categorical variables, text, pictures, videos, audio inputs are eventually converted to array of numbers. Day 6 Revision - 2.8 Scaling Data and 2.9 Encoding categorical data The point of scaling Data is transforming it to fit within some range or scale say 0 - 1 or 1-100. It doesn't affect the algorithms because every value is scaled same way. It can speed up the training process

  Been a long while here. Been up and running as usual, working my butt off to make a living and see how I can contribute to making the world a better place the little way I can.  So a lot has happened since the last time I wrote here and i am grateful for everything. I got selected for the Phase 1 of a Machine Learning challenge course sponsored by Microsoft in collaboration with Udacity and it's been great so far. My network of international friends and acquaintances really grew by a significant percentage and I have had the opportunity to share some of m knowledge and skills with lots of people around the world as a student leader. Machine Learning is really awesome stuff that is poised to create a lot of opportunities in today's world while topping over a lot of traditional/manual processes. And I think you should pay attention it. That's what i have been doing. And I ave been thinking of a way to connect ML/AI to Motivating and inspiring the best they can be. How can

I am really inspired and excited to be writing this and I think the inspiration to write it is coming at a very good time. If you pay close attention to the people around you and to happenings around the world, you will find that a couple of people are unhappy. Statistics show that about 1 in 4 people are mentally depressed. Why are they unhappy? They are thinking of problems, thinking of how they will get to where they desire to be, bothered about the things that they are yet to have, the kinda relationships they dream of and etcetera. No one is expected to be happy all the time, however one needs to at least feel good most of the time regardless how things may seem. So how can these unhappy people (who are constantly bothered about the things they desire) learn to be happy? I have a simple tip today which I believe will go a long way to help them. If you are already feeling good about yourself most of the time, you can share this tip with someone who you know is mostly down and adopt

So after so many months without visiting his blog, I tried to visit boldanddetermined.com for some fired up articles only to get a surprise.. that the blog has been permanently closed and then there's podcast following from Vic Pride (now Brother Nicholas) claiming that He's now Born again and has given his life to Jesus Christ. I didn't know how to feel. Whether it's good news or bad news will ultimately be up to us, but I just think I should share my thoughts about it here. But before that a brief background story. Victor Pride has been running the motivational blog bold and determined since 2011 and he has actually inspired and motivated a lot of young men and women to break out lazy attitudes/habits to live the life of their dreams.  Even though, I never really agreed with quite a number of his ideas about God, religion, the government, women etc, I still saw the truth in some of the things he said. And he had a very unique way of writing with gives you that adrenal

Hi guys, Been a while! Lots of things happening around the world right now and nobody even knows what will happen next! There are ongoing protests right now over racism and police brutality and Covid 19 is still making headlines. These are really tough times for everyone as economies are struggling and social distancing is becoming a norm. Despite these present realities, you don't have to alienate yourself from people or keep too far away from them because of social distancing. Right now more than ever, it is very important you show people that they matter to you and you value their relationship and friendship. Here are six tips you can take advantage of: 1. Engage them from time to time We are all busy, that's true! I agree to that statement even though (on a lighter note) I think most of us are busy doing nothing.. haha. However, no matter how busy we are or think we are, we must discipline ourselves to make out time to engage with the people we care about. We all have 24 hr

So there's this insight I'm getting in my mind right now and I just wanted to share: . Some people think they can only change the world when they do the big things, like getting to some high govt positions, starting a global movement or inventing something that has never been seen before etc. . But they forget that with every action we take everyday of our lives we are actually changing the world for every one of us. No matter how little or insignificant you think that action is. . Some things as trivial as saying some comforting words to someone who's hurting, sharing opportunities that may be helpful to another person, smiling at someone and even just dropping a helpful comment to fix another person's problem are actually changing the world in many ways than we can imagine. . Look back at your own life and see how your present situation is a function of the input of everyone you've come across. From you parents advice to the books you've read, movi

Nobody will tell you that they have been applying to various opportunities and getting rejection mails..☹️ you will only hear the good news when the opportunity finally succeeds.🙂 . Nobody posts their ugly pictures 😣 on Facebook or IG.. they won't tell you how many pictures they must've have taken and deleted before settling for the one they finally post for you to see.😁 . Nobody tells you how many times they feel low, how many times they cry in private or how many times they feel like shit.😖 But whenever they come out to the public, you get to see happy, lively, charismatic and smiling faces.🕺🏽 . No one posts pictures of when they were reading or studying hard to pass in school. But when the results come out, you will be the first to hear who got A, who got first class.. etc . The entrepreneur will not tell you how many times he felt like quitting 👎🏼during the early stages of his business..but when the business kicks off.. you will hear the net worth of the co

When we were little kids, sometimes we will see a very dirty car parked outside and in our little minds, the stuff doesn't look right to us. Cars are supposed to be washed and taken care of. It looks absurd to us. . So what comes to mind? We go closer, look left and right to confirm no one older is watching and we write "pls wash me." The ones with better GST skills will add "..I am dirty" to it. Plenty of us have been on this table. . My mind cast back to this thing because I saw it today. As innocent children, there was a consciousness in us to at least attempt to make things right. If something doesn't look right, we tried to make it right by in this case "writing something". Thereby "speaking" on behalf of the vehicle to whoever owns it. . This innate drive to make things better is why children don't keep grudges for too long. They play and quarrel, next minute, they're together again. Chaos and absurdity is naturally a

Sometimes in the middle of all these daily struggle and aspirations to become something, to do something, to make impact, to be successful, to get married, and etc, I always ask myself the big question: why? . Why do we do these things? Is it our way of finding meaning in life? Is it our way of keeping busy so we avoid our thoughts? Is it just the way the world is? Is it just to keep up with what our peers are doing? The big question is why?! . Often times, we don't get to ask ourselves this question. We just follow the trend and we try to become like other people or do things just because other people are doing them. This leads to a lot of confusion. The trend is not always right for you! . The danger of just doing things because you're pressured to do so without really understanding why you're doing it is that you will eventually find yourself dissatisfied and discontented, and when that happens you will not even be motivated to continue because you're like: wh