Shreya's AI-ML-001 course work. Lv 2

AIML Level 1

9 / 9 / 2023

Task 1: 3-D PRINTING\n\n1. Find and download the desired STL file from online platforms like Thingiverse or Fusion 360.\n2. Use slicing software like Creality Slicing Software version 4.8.2 to slice the STL file into layers that can be printed.\n3. Adjust the settings, such as scaling and material usage, and generate G-code, which is the language used by 3D printers to create the object.\n4. Copy the G-code to an SD card and insert it into the 3D printer to start the printing process.\n5. Wait for the printing process to finish\n\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 2: API\n\n1. An API (Application Programming Interface) is a type of software interface that allows two or more computer programs to communicate with each other.\n2. We are using an API to access weather data, specifically the Open Weather API.\nThe Open Weather API allows us to retrieve essential weather data for a specific location with just one API call.\n3. We made the code dynamic by placing it inside a function that takes a city parameter and replaces the API key token with our own.\n4. We then integrated this dynamic code into a website application, allowing users to input any city or place and see the current weather displayed accurately.\n\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 3: Github\n\n1. We began by forking a given repository, and then cloning it to our local machine using the 'git clone' command on Git Bash.\n2. Next, we created a new repository and a new branch, and used the 'git checkout' command to switch to the new branch before making any changes to the code.\n3. We then opened the 'main.py' file of the cloned repository using VS Code and checked for any errors in the code.\n4. After identifying errors, we corrected them and used the 'git add .' command to stage the changes made for the next commit.\n5. Finally, we used the 'git commit --push origin' command to take a snapshot of the changes made and push them to GitHub. We were prompted to enter our GitHub username and email in the terminal before pushing the changes.\n\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 4: Working with the Ubuntu command line.\n\n1. Create a folder named test using the mkdir /tmp/ command.\n2. Cd into that folder using cd /tmp/\n3. Create a blank file without using any text editor(mkdir )\n4. List the files in that folder using “ls”\n5. Using for loop we created 2600 folders in this folder where each folder is named like le1 le2 etc.\n6. We used cat file1.txt>>file2.txt to concatenate two text files containing any random text and display them on the terminal.\n\n\n\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 5: Kaggle Titanic ML Competition\n\n1. The competition involves using machine learning to create a model that predicts which passengers survived the Titanic shipwreck.\n2. To participate, we need to join the competition, read the challenge description, accept the Competition Rules, and gain access to the competition dataset.\n3. After gaining access to the data, we can download it and build machine learning models on it using tools such as Kaggle Notebooks (Jupyter Notebooks) locally or on the Kaggle platform.\n4. Once we have built our model and generated a prediction file, we can make a submission by uploading the prediction file to the competition on Kaggle. The submission will be scored for accuracy and we can see how well our model performed compared to others.\n\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 6: Working with Pandas and Matplotlib\n\n1. Pandas is a package commonly used to deal with data analysis. It simplifies the loading of data from external sources such as text files and databases.\n2. First, download the data by passing the download URL to pandas.read_csv(). Pandas has two core data structures used to store data: The Series and the DataFrame.\n3. The series is a one-dimensional array-like structure designed to hold a single array\n4. The DataFrame represents tabular data, a bit like a spreadsheet matplotlib is a Python package used for data plotting and visualisation.\n\n\n\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 7: TinkerCad\n\n1. Arduino is a platform for creating open-source electronics projects. It is equipped with an ATmega328 8-bit Microcontroller which enables it to read inputs from various sensors and execute instructions sent to it.\n2. The setup process involves:\nConnecting the Echo pin of the sensor to the D2 pin of the Arduino and the Trig pin to the D3 pin of the Arduino.\nSelecting the board and port in the Tools menu, verifying and compiling the code, and then uploading it to the Arduino Uno R3 board.\nMonitoring the output in the Serial monitor.\n3. To interface with an LCD display, we need to:\nInstall the driver library for the Liquid Crystal Display.\nImport the \LiquidCrystal_I2C.h" header file in the code.\nConnect the SDA pin of the LCD display to the SDA pin of the Arduino board and the VCC to the 5V pin and GND to the GND pin.\n\n\nhttps://photos.google.com/photo/AF1QipMFHwOpflbTm6oNBaP1_1CrrX8UbHe73KQT08Pc\n\n--------------------------------------------------------------------------------------------------\n\n## Task 8: Soldering\n\n1. Insert the LED leads into the circuit board holes and bend the leads outward at a 45-degree angle.\n2. Turn on the soldering iron and set the heat control to 400'C.\nHold the tip of the iron to the copper pad and resistor lead for 3-4 seconds to heat the joint.\n3. Touch the solder to the joint, not directly to the iron tip.\n4 .Remove the soldering iron and let the solder cool naturally, without blowing on it.\nOnce cool, snip the extra wire from the leads.\n\n\n--------------------------------------------------------------------------------------------------\n\n## Task 9: LED Toggle Using ESP32\n\n1. We are using the ESP32 DEVKIT DOIT board with 38 pins. Start by building the circuit. Connect two LEDs to the ESP32.\n2. Copy the code to your Arduino IDE. We need to tweak this code for changing login credential for your available WiFi network.\n3. Setting Your Network Credentials: We need to modify the following lines with your network credentials: SSID and password.\n4. After uploading the code, open the Serial Monitor at a baud rate of 115200.Press the ESP32 EN button (reset). The ESP32 connects to Wi-Fi, and outputs the ESP IP address on the Serial Monitor. \n5. Copy that IP address to access the ESP32 web server. Click the buttons to control the LEDs.\n\n \n\n--------------------------------------------------------------------------------------------------\n\n\n\n"