100 Days of Machine Learning Journey: Week 1 Recap

100 days of ML

The Birth of the 100 Days of ML Journey

It all began with the idea to challenge myself and accelerate my career in machine learning by embarking on a #100DaysOfCode journey, tailored specifically for AI, ML, DL, and Python engineering.

With the help of ChatGPT, an AI model, I crafted a 100-day plan that would take me from beginner to advanced level, creating real-world projects each day until I secured a meaningful career in machine learning.

ChatGPT helped me to design a spreadsheet spanning 100 days, meticulously organizing each day’s Challenge Title, Challenge Description, Anki Interview Q/A, and progress tracking across several areas, including GitHub, Twitter, networking, CodeWars, and blog publishing. With the roadmap laid out, my 100 Days of ML odyssey commenced, fueled by dedication, curiosity, and the desire to learn and grow.

At the last minute, understanding that Python was essential to the learning process as well, I doubled the workload and joined up with 100 Days of Code: Python 2023 Bootcamp with Dr. Angela Yu from the London App Brewery.

So here I am with you today, sharing this engrossing project…


Embarking on an epic journey, the 100 Days of ML challenge is all about diving headfirst into the world of machine learning, deep learning, and Python programming. Every day, I’ll be sharing my progress, creating real-world projects, and showcasing my skills on social media until I’m hired. Let’s get this show on the road! 🚀

Day 1: Setting Sail on the ML Voyage

  • Built the ultimate dev environment: Python, Jupyter Notebook, Git, TensorFlow, Keras! It’s like a machine learning Batcave 🦇
  • Grasped the nuances of supervised vs unsupervised learning, and added them to my Anki deck (like a knowledge treasure chest 🏴‍☠️)
  • Crushed a CodeWars challenge 💪 My coding skills are leveling up already!
  • Explored the world of data analytics, pandas, and CSV files. Pandas were dancing in my head! 🐼💃

Feeling: Energized and ready to conquer the ML world!

Day 2: Pythonista in the Making

  • Embraced my inner Pythonista and dived into Python concepts 🐍
  • Built a sleek Tip Calculator in Python. Awkward dinner situations? Not on my watch! 🍽️
  • Plunged into the depths of pandas with “Deep Diving into Pandas” 🌊🐼
  • Tackled two CodeWars challenges, sharpening my coding ninja skills 🥷
  • Added a new ML interview question to Anki: Types of Machine Learning, and reviewed the deck for knowledge retention 🧠

Feeling: Thrilled and determined to keep growing my ML prowess!

Day 3: Overcoming Adversity

  • Woke up with a headache, but pushed through like a champ 💪
  • Completed the Numpy course on AI Planet, unlocking a new level of mastery 📜
  • Finished week 3 & 4 of Deeplearning.ai’s ‘Intro to TensorFlow’ with an MNIST digit classification project. Hello, digits! 🤖
  • Applied to ML internships, started Cognizant AI Virtual Experience Program & GirlsWhoCode Interview Prep 💼
  • Networking events? Check! Registered for Quantum Computing & Machine Learning and GDI Virtual Career Fair 🤝
  • Completed Day 3 of Python Bootcamp, focusing on control flow and logical operations. Built a “Treasure Island” choose-your-own-adventure game. 🏝️
  • Created a new interview question for my Anki deck: Differentiate between regression and classification. Reviewed my existing cards. 📚
  • Completed one CodeWars challenge. ⚔️

Feeling: Proud for persevering and making progress, despite the headache

Day 4: Visualizing My Way to ML Success

  • Unleashed my inner Picasso with data visualization using Matplotlib and Seaborn 🎨
  • Explored the vibrant world of graphs and plots with Gunnika Batra at AI Planet 🌐
  • Added a thought-provoking interview question to Anki: ML vs Deep Learning, and reviewed the deck 🤔
  • Kept mental health in check with a productive therapy session. Mental health is important, and taking care of yourself while pursuing a challenging goal like learning machine learning is essential 💆‍♀️

Feeling: Inspired by the power of visualization and excited for the days ahead! It’s amazing how visualizations can help make sense of data and communicate insights more effectively.

Day 5: Double Trouble

  • Played catch-up and doubled down on learning. Bring it on! 💥
  • Dabbled with deep learning in TensorFlow and Keras, creating a neural network for the Pima Indians diabetes dataset, inspired by Jason Brownlee, PhD at Machine Learning Mastery 🧬
  • Deep dived into Deep Learning course on Ai Planet
  • Crushed both Day 4 and Day 5 Python projects: Rock, Paper, Scissors and a Password Generator 🎸📝✂️
    • For the Day 4 project, I created a Rock, Paper, Scissors game using Python’s ‘random‘ library to generate computer choices and taking user input to play the game. The program then determines the winner based on the rules of the game.
    • For Day 5, I built a Password Generator that takes user input for the desired length and composition of the password (letters, numbers, and symbols). The program uses Python’s ‘random‘ library to generate a secure and random password based on the user’s preferences.
  • Interview prep time! Added a new Anki question: What is a confusion matrix, and why do you need it? 🧐
  • Signed up for my first hackathon, #PromptHacks23 GPT-4 Hackathon, organized by @VoiceFlowHQ and @ReamBraden. I’m excited to participate and put my newfound skills to the test 💪

Feeling: Pumped to have caught up and ready to tackle more challenges! Despite a busy day filled with work, grocery shopping, AWANA, and basketball practice, I managed to stay on track with my learning goals. This journey is teaching me the importance of dedication and time management. Onward to Day 6!

Day 6: Mastering the Art of Gradient Descent

  • Delved into loss functions, gradient descent, and the magic of linear regression 📉
  • Stumbled upon an unexpected exploit on my favorite learning website 🕵️‍♀️
  • Created a new interview question for my Anki deck: AI, ML, and Deep Learning – a trifecta of knowledge! 🧪
  • Completed Day 6 of the Python Bootcamp, focusing on functions and Karel. Built an “Escape the Maze” game 🏰
  • Stayed sharp by completing a Codewars challenge and reviewing my Anki deck 📚

Feeling: Empowered by new knowledge and eager for the next adventure!

Day 7: CNNs – The Secret Sauce of Image Recognition

  • Dived into the fascinating world of convolutional neural networks (CNNs) and built a simple CNN for image classification using the MNIST dataset 📸
  • Finished the deeplearning.ai Intro to TensorFlow course and started the Convolutional Neural Networks course 🚀
  • Created a classifier for the Cats v Dogs dataset of 25k images. Who’s a good ML model? 🐶🐱
  • Completed Day 7 of the Python Bootcamp and built a Hangman game. Watch out, secret words! 🎩
  • Crushed 3 CodeWars challenges and added a new Anki question: What’s the trade-off between bias and variance? 🎲
  • Started new blog series to document my learnings from the Cognizant Artificial Intelligence Internship

Feeling: Enthralled by the power of CNNs and looking forward to unlocking more ML mysteries!

Week 1 Wrap-up

What a wild ride! From setting up the ultimate dev environment and diving into Python to exploring data visualization, deep learning, and convolutional neural networks, this week has been a rollercoaster of learning, challenges, and growth. I’m feeling more enthusiastic than ever about my journey in machine learning and can’t wait to see where the next 93 days take me! Let’s keep the momentum going! 🎢💯

Remember to follow along on Twitter and GitHub to see each day’s progress and projects, and feel free to join the journey or share your insights! 🌟

I’ll see you in Week 2 for the continuation of our 100 Days of ML voyage!

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