Karen Janice Mazidi
Karen Janice Mazidi
  • Видео 82
  • Просмотров 177 635
CA04 - MIPS and machine code
Converting MIPS instructions to machine code, and reverse engineering machine code to MIPS instructions; MIPS instruction formats
Просмотров: 6 632

Видео

CA01 - Introduction to Computer Architecture
Просмотров 16 тыс.4 года назад
What is Computer Architecture?
nlp25 - Embeddings
Просмотров 2424 года назад
Content from Chapter 25 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Training your own embeddings or using pretrained embeddings live GloVe, ELMo, BERT.
CA23 - Dependability and security
Просмотров 8254 года назад
Parity and ECC for error detection; virtual machines, containers and cloud; hardware vulnerabilities
nlp26 - Sequence to sequence models
Просмотров 2204 года назад
Content from Chapter 26 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Encoders and decoders for seq-2-seq models.
nlp24 - Deep Learning Variations
Просмотров 2654 года назад
Content from Chapter 24 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Adding an Embedding layer in Keras: RNN, CNN, LSTM, GRU in Keras
nlp23 Deep Learning
Просмотров 2954 года назад
Content from Chapter 23 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Deep learning for text classification with Keras; Keras API; Keras Functional API
nlp21 - Logistic Regression
Просмотров 3254 года назад
Content from Chapter 21 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Logistic Regression for text classification; underfitting and overfitting; gradient descent; odds versus probability; log odds; sigmoid function
nlp22 - Neural Networks
Просмотров 3444 года назад
Content from Chapter 22 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Neural networks in sklearn; perceptrons; neurons; layers; activation functions; feed forward network; back propagation; epochs; network design
nlp19 - Converting text to data
Просмотров 4574 года назад
Content from Chapter 19 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Using sklearn CountVectorizer() and TfidfVectorizer()
nlp20 - Naive Bayes
Просмотров 3634 года назад
Content from Chapter 20 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Running Naive Bayes in sklearn for text classification. Metrics: accuracy, precision, recall, Kappa, ROC and AUC.
nlp17 ML intro
Просмотров 4174 года назад
Content from Chapter 17 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 An overview of machine learning; supervised v. unsupervised learning; terminology
nlp18 Libraries
Просмотров 3744 года назад
Content from Chapter 18 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 An introduction to NumPy, pandas, Seaborn, sklearn.
nlp14 - Vector space model
Просмотров 7134 года назад
Content from Chapter 14 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Implementing a vector space model from scratch or using sklearn. Explanation of cosine similarity.
nlp15 topic modeling
Просмотров 2854 года назад
Content from Chapter 15 of Exploring NLP with Python, available on Amazon: www.amazon.com/dp/B08P8QKDZK/ Second edition is available on VitalSource: www.vitalsource.com/products/exploring-nlp-with-python-kjg-mazidi-v9798991818803 Topic modeling with gensim.
nlp12 - Corpora
Просмотров 4304 года назад
nlp12 - Corpora
nlp13 - Information Extraction
Просмотров 1,3 тыс.4 года назад
nlp13 - Information Extraction
nlp - syntax parsers
Просмотров 3384 года назад
nlp - syntax parsers
nlp09 - CFG
Просмотров 6664 года назад
nlp09 - CFG
nlp10 syntax parsers
Просмотров 6994 года назад
nlp10 syntax parsers
nlp08 - ngrams
Просмотров 5844 года назад
nlp08 - ngrams
nlp07 - Relationships between words
Просмотров 7084 года назад
nlp07 - Relationships between words
nlp06-POS tagging
Просмотров 1,7 тыс.4 года назад
nlp06-POS tagging
nlp05-Words and Counting
Просмотров 5184 года назад
nlp05-Words and Counting
nlp03-NLTK
Просмотров 8374 года назад
nlp03-NLTK
nlp04-Linguistics
Просмотров 4664 года назад
nlp04-Linguistics
nlp02-Python
Просмотров 6614 года назад
nlp02-Python
nlp01-Welcome to Natural Language Processing
Просмотров 1,8 тыс.4 года назад
nlp01-Welcome to Natural Language Processing
ML27 - Markov Models to Reinforcement Learning
Просмотров 2034 года назад
ML27 - Markov Models to Reinforcement Learning
ML26 - Bayes network
Просмотров 2074 года назад
ML26 - Bayes network

Комментарии

  • @lucyheartfilia6948
    @lucyheartfilia6948 2 месяца назад

    When I'm really tired with MIPS, I find this video. It's really help me ❤ Thank you, teacher. It's 2:37am in my country 😢 You are the first woman teacher that I learn. You influence me so much!!! Thank you ❤

    • @KJMazidi
      @KJMazidi 2 месяца назад

      You got this!

  • @Bloxicorn
    @Bloxicorn 3 месяца назад

    Thank you, I'm behind on my comp org and arch class and your videos are helpful. This one is just review for me but it's helpful to see MIPS with assembly code as my professor doesn't give any code examples.

    • @KJMazidi
      @KJMazidi 3 месяца назад

      Glad it was helpful!

  • @박의찬-p5g
    @박의찬-p5g 7 месяцев назад

    Nice

  • @madelineluray7553
    @madelineluray7553 8 месяцев назад

    thank you, this was very helpful :)

    • @KJMazidi
      @KJMazidi 4 месяца назад

      Glad it was helpful!

  • @DriveTru-US
    @DriveTru-US Год назад

    Hello dear professor , I am MD HELAL HOSSEN , I am taking you NLP course this spring 2024. I learn a lot from your video.

  • @armaankhatri3608
    @armaankhatri3608 Год назад

    great explanation

  • @xxnotmuchxx
    @xxnotmuchxx Год назад

    instead of typing the code, is there a place to copy code? or where can i get those ppts?

    • @KJMazidi
      @KJMazidi Год назад

      You can find some of it in my GitHub: github.com/kjmazidi

  • @Satya-jr6ml
    @Satya-jr6ml Год назад

    This deserves much more views, professor! I'm taking this course in my university right now and I don't understand one bit of what my professor talks about! Thank you for this!

  • @praneetkomandur5313
    @praneetkomandur5313 Год назад

    thank u

  • @Octavian999
    @Octavian999 Год назад

    Thank you so much professor, this was very helpful.

  • @codehorror8076
    @codehorror8076 Год назад

    Interesting fact: The R3000A in the PS1 didn't have a FPU.

  • @codehorror8076
    @codehorror8076 Год назад

    Thanks Karen. Watching this because I'm doing MIPS of a PS1. You're a star!

  • @daviddeng9743
    @daviddeng9743 Год назад

    Thanks Professor Mazidi, I'm having a hard time learning from my current professor and your videos are making it easy for me to keep up in class

  • @practicefirsttheorylater
    @practicefirsttheorylater Год назад

    finally a good explanation of signed and unsigned

  • @qt6969
    @qt6969 Год назад

    Thank you professor!

  • @sniro1984
    @sniro1984 2 года назад

    I wish I could be in your class, your students are so lucky! :) for the exercise in 14:32 this is what I did : lw $t1, a lw $t2, b la $t0, a sw $t1, 4($t0) sw $t2, 0($t0) Is there a simpler way ?

  • @beckembrown7002
    @beckembrown7002 2 года назад

    When you say copy through the first 1, do you mean that we copy from the right until we reach the first 1 than flip the remaining bits on the left of that 1?

  • @caine7024
    @caine7024 2 года назад

    explained very simply and quickly! it's perfect

  • @altblogru
    @altblogru 2 года назад

    Thank you very much for video!

  • @slazy9219
    @slazy9219 2 года назад

    Great explanation! Thanks :)

  • @rasikpokharel77
    @rasikpokharel77 2 года назад

    ily. I've learned more computer architecture from these videos in a few hours than all semester.

  • @ashleylove6840
    @ashleylove6840 2 года назад

    Thank you so much! You are so good at explaining things

  • @DailyDemo1
    @DailyDemo1 2 года назад

    its totally amazing

  • @DailyDemo1
    @DailyDemo1 2 года назад

    thanks for your content

  • @saeedbarari2207
    @saeedbarari2207 3 года назад

    thanks.

  • @varinderbarmi
    @varinderbarmi 3 года назад

    wonderful explanation!!! thank you :)

  • @cheetahcheetos7497
    @cheetahcheetos7497 3 года назад

    you're the best

  • @luispedromorales3242
    @luispedromorales3242 3 года назад

    Great video! Very helpful, thanks

    • @KJMazidi
      @KJMazidi 3 года назад

      Glad it was helpful!

  • @antonchigurh8102
    @antonchigurh8102 3 года назад

    pycharm > jupyter notebook

  • @joel2527
    @joel2527 3 года назад

    Hey I need help with my code

  • @pernarhvincent907
    @pernarhvincent907 3 года назад

    this is good !!

  • @cerealgrapist7386
    @cerealgrapist7386 3 года назад

    im still lost but at least its not looking as scary anymore lol

  • @proomm986
    @proomm986 3 года назад

    This is the best explanation about this topic that I can find on YT

  • @gopavaramsaimadhuree520
    @gopavaramsaimadhuree520 3 года назад

    superb explanation thank you

  • @amaanrampath4100
    @amaanrampath4100 3 года назад

    Thank you for the nice explanation

    • @KJMazidi
      @KJMazidi 3 года назад

      You are welcome!

  • @opicaskorica564
    @opicaskorica564 3 года назад

    Absolutely fantastic video! I couldnt find main control unit logic anywhere on the internet, you helped me very much

    • @KJMazidi
      @KJMazidi 3 года назад

      Great to hear!

  • @mazinashfaq631
    @mazinashfaq631 3 года назад

    Very clear explanation! Thank you.

    • @KJMazidi
      @KJMazidi 3 года назад

      Glad it was helpful!

  • @4edgy8me
    @4edgy8me 3 года назад

    Great video!

  • @NOLAMarathon2010
    @NOLAMarathon2010 3 года назад

    Regarding the code shown at 6:59. As you've written it, it doesn't work for me. These are the errors I get on lines 11, 12, 13 and 14: 11 --> Too few or incorrectly formatted operands. Expected: lw $t1,-100($t2) 12 --> Too few or incorrectly formatted operands. Expected: lw $t1,-100($t2) 13 --> Too few or incorrectly formatted operands. Expected: sw $t1,-100($t2) 14 --> Too few or incorrectly formatted operands. Expected: sw $t1,-100($t2)

    • @KJMazidi
      @KJMazidi 3 года назад

      These are pretty standard lw and sw instructions. Did you put in the commas? Did you define a, b, c, d in the data section? Are you using MARS?

  • @efi13efi
    @efi13efi 4 года назад

    The guy at the end of the line!

  • @veganphilosopher1975
    @veganphilosopher1975 4 года назад

    Next time I'm at a ML conference proceeding I'll be thanking u

  • @HH-ip5zc
    @HH-ip5zc 4 года назад

    What is the control signal for lbu ? It is the same of lw ?

    • @KJMazidi
      @KJMazidi 4 года назад

      This simplified MIPS implementation doesn't have the lbu instruction, but if it did, the control signals would be the same.

    • @HH-ip5zc
      @HH-ip5zc 4 года назад

      Ok Thx ☺️

  • @finnwilliams1808
    @finnwilliams1808 4 года назад

    aayyhh quotes are back, I was missing them

  • @habibollalatifizadeh2842
    @habibollalatifizadeh2842 4 года назад

    Hi Dear Dr. Mazidi, Thanks. Your channel was very helpful for me. Would you please make a video on Bayesian Network, specially in "kruskal.test" ,"pairwise.wilcox.test" and "anova test" ?

  • @veganphilosopher1975
    @veganphilosopher1975 4 года назад

    I havent used java in like two years lol

  • @veganphilosopher1975
    @veganphilosopher1975 4 года назад

    For those of you that forgot Cosine Similarity ( Number of like items ) / [ SQRT ( x1 ^ 2 + ... + xn^2) * SQRT( x1^2 + ... + xm^2 ) ]

  • @benjaminray4833
    @benjaminray4833 4 года назад

    Best explanation of Cosine Similarity I've ever seen. Thanks Dr. Mazidi.

  • @guljemalrahmanova1890
    @guljemalrahmanova1890 4 года назад

    "Information is not knowledge"

  • @guljemalrahmanova1890
    @guljemalrahmanova1890 4 года назад

    Wow the last quote was very impressive!